the uk’s research and innovation infrastructure: landscape ......5 chapter 10: physical sciences...

The UK’s research and innovation infrastructure:Landscape Analysis

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Executive summary 6

Chapter 1: Introduction 8 1.1 Scopeanddefinitionofresearchandinnovationinfrastructure 9 1.2 Infrastructurediversity 10 1.3 Scaleandcoverage 11 1.4 Questionnairemethodology,limitationsandpotentialbias 13

Chapter 2: Overview of the landscape 15 2.1 Thecross-disciplinarynatureofinfrastructures 17 2.2 Largescalemulti-sectorfacilities 18

Chapter 3: Lifecycle 21 3.1 Concept 22 3.2 Currentlifecyclelandscape 23 3.3 Evolutionofthelandscape 26 3.4 Lifecycleandplanning 26

Chapter 4: International collaboration and cooperation 28 4.1 Internationalcollaboration 29 4.2. Staffing 29 4.3 Internationaluserbase 30

Chapter 5: Skillsandstaffing 32 5.1 Numbers 33 5.2 Roles 36 5.3 Staffdiversity 36

Chapter 6: Operations 38 6.1 Set-upcapitalcosts 39 6.2 Sourcesoffunding 41 6.3 Primaryfundingsource 42

Chapter 7: Measuringusageandcapacity 43 7.1 Usage 44 7.2 Measuringcapacity 45 7.3 Managingcapacity 47 7.4 Barrierstoperformance 49

Chapter 8: Links to the economy 52 8.1 Workingwithbusinesses 53

Chapter 9: Biologicalsciences,healthandfoodsector 56 9.1 Currentlandscape 57 9.2 Interdependencywithe-infrastructure 63 9.3 Engagementwiththewidereconomy 63

Contents

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Chapter 10: Physicalsciencesandengineeringsector 65 10.1 Thecurrentlandscape 67 10.2 Characterisingthesector 69 10.3 Theimportanceofinternationalcollaboration 71 10.4 Impacts 71

Chapter 11: Socialsciences,artsandhumanitiessector 73 11.1 Formandfunctionofinfrastructures 74 11.2 Researchobjects(physicalandvirtualresources) 76 11.3 Impactandoutputs 78 11.4 Socialsciences,artsandhumanitiesinfrastructures’users 80

Chapter 12: Environment sector 82 12.1 Characteristicsofthelandscape 83 12.2 Impactandoutcomesfortheeconomy,industryandpolicymaking 86 12.3 E-infrastructureandDataneedsofthesector 89

Chapter 13: Energysector 90 13.1 Currentlandscape 91 13.2 Recentinvestments 93 13.3 Theroleofdataande-infrastructureinthesector 95 13.4 Energyasakeyeconomicsector 95

Chapter 14: Computational and e-infrastructure sector 98 14.1 Currentlandscape 99 14.2 E-infrastructure,dataandinnovation 103

Annex A: Definitionofresearchandinnovationinfrastructure usedwithinthisprogramme 105

Annex B: Methodology 107

Acronyms and abbreviations 112

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Executive summaryResearchanddevelopment(R&D)hasacentralroletoplayindrivingeconomicgrowth.MeetingtheambitionsoftheIndustrialStrategy,includingdeliveringthefourGrandChallengesandthetargettoincreasetotalR&Dinvestmentto2.4%ofGDPby2027,requiresinvestmentininfrastructureasthebasisofourresearchandinnovationlandscape1.TodaytheUKisgloballyrecognisedasaleaderinresearchandinnovation,havingthemostproductivesciencebaseintheG7basedonfield-weightedcitationsimpactandresearchpapersproducedperunitofR&Dexpenditure2,3.Every£1spentonpublicR&Dunlocks£1.40ofprivateR&Dinvestment4,togetherdelivering£7ofnet-economicbenefittotheUK5.Wearehighlysuccessfulintranslatingknowledgeintoreal-worldsocietal,economicandinternationalbenefits.EstimatessuggestthatmorethanhalfoftheUK’sfutureproductivitygrowthwillbedrivenbytheapplicationofnewideas,researchandtechnologytocreatenewprocesses,productsandservices6.

Thesesuccessesareinlargepartfoundedonanetworkofinternationallycompetitive,high-qualityandaccessibleresearchandinnovationinfrastructures.TheUKresearchandinnovationinfrastructurelandscapeisdiverse,fromlarge-scalephysicalresearchfacilitiessuchassynchrotrons,researchshipsandscientificsatellites,tonetworksofimagingtechnologiesandknowledge-basedresourcessuchasscientific,culturalorartisticcollections,archives,clinicalandpopulationcohorts,dataandcomputingsystems.ThisreportprovidesanoverviewofthecurrentlandscapeusingthebroadsectorsusedbytheEuropeanStrategyForumonResearchInfrastructures(ESFRI).ItbuildsontheInitialAnalysis7publishedinNovember2018,fillingingapsincoverageandundertakingadditionalanalysistoexploreissuesinmoredepth.

A snapshot of the UK landscapeOurquestionnaireapproachandanalysishaveidentifiedover750infrastructuresofregional,nationalandinternationalsignificance,527ofwhichareofnationalorinternationalsignificance.InfrastructuresarelocatedineveryregionoftheUKandaroundfiftyareoverseasinatleasttwenty-fivedifferentcountries.Eighty-fourpercentarehousedwithinotherinstitutions,

primarilyhighereducationinstitutions(HEIs).Someinfrastructures,suchasresearchships,planesorsatellites,havenofixedlocation.Othersaredistributedbetweenmultiplesites.

Infrastructuresofallsizesrequirestaffwithhighlyspecialisedskills.Thenationalandinternationalinfrastructuresrespondingtoourquestionnairesemployjustunder25,000full-timeequivalentstaff(FTEs)intheUK.Infrastructuresneedarangeoffunctionstooperate,includingresearch,technicalandotherroles(e.g.managerial,administrative).Fiveofthesixsectorshadmorethanthreequartersofstaffinresearchandtechnicalroles.Onaverage,functionsaresplitasfollows:38%ofstaffintechnicalroles,33%inresearchand29%inotherroles.

Collaboration with business and the wider economyOverthreequartersofinfrastructuresconductsomeworkwithUKbusinesses,with17%conductingmostoralloftheirworkinthisway.Atleastfifteeninfrastructuresidentifiedthattheyworkwithorcontributetoeveryoneofthefortyeconomicsectorgroupings,indicatingthebreadthoftheseinteractions.Acrossthelandscapethemosthighlycitedeconomicsectorinteractionsoutsideofresearchandeducationwerepublicpolicy,healthservices,energyutilities,instrumentationmanufacture,agriculture,communications,computinganddataservices,pharmaceuticals,electronicsmanufactureandaeronauticaltransport.

Modernresearchandinnovationisrarelysingledomain-led.Ninety-twopercentofinfrastructuresworkacrossmorethanoneresearchsectorwiththecomputationalande-infrastructuresectorhavingthebroadestreach.Someinfrastructuresaredesigned fromtheiroutsettobelarge-scalefacilitiesservingmultiplesectorswithapplicationsacrosstheeconomy.

International collaborationTheSmithReviewhighlightstheimportanceofinternationalcollaboration.Ninety-twopercentofinfrastructurescollaboratewithinternationalpartners.Theyplayanimportantroleinthemobilityoftalent,actingasamagnettoattractleadingresearchersandinnovators

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fromacrosstheworld.Twenty-sevenpercentofinfrastructures’staffwerefromoverseaswithcomputationalande-infrastructurehavingthegreatestrelianceonnon-UKnationalsat39%.Thirty-ninepercentofusersofinfrastructuresalsocomefromoutsidetheUK.Oftenthisisbecausethereisnosimilarcapabilityelsewhere,theinfrastructurebeingintegraltointernationalcollaborationandthequalityofsupportonofferatUKinfrastructures.

Long-terminvestmentsOurdatademonstratestheUK’slonghistoryindevelopingresearchandinnovationinfrastructureswithsubstantialinvestmentinnewcapabilityapparentoverthelasttwentyyears.Theearliestinfrastructurestendedtobecollectionshousedinmuseums,librariesorgardens.Socialandpoliticaldriversledtothefirstagriculturalandenvironmentalinfrastructuresappearingearlyinthetwentiethcentury.The1950s,1960sand1970ssawtheestablishmentoflargeinfrastructuressuchasatConseilEuropéenpourlaRechercheNucléaire(CERN)andtheBritishLibrary.Bythe1980slargecomputationalanddatainfrastructuresweremorecommonandthe1990sthroughtothe2000ssawthediversityofthelandscapecontinuetoexpandwithagreaterfocusoninnovation,imaging,autonomoussystems, the‘omics’andquantumtechnologies.

Infrastructuresarelong-terminvestmentsand60%haveoperationallifespansofovertwenty-fiveyears.Infrastructuresinareasreliantontechnologywithrapidevolutionrates,suchase-infrastructure,tendtohaveshorterlifespans.Inotherareas,suchasdataandcollections,infrastructuresincreaseinvalueovertime.However,largelyduetotheuncertaintyaroundfundingcycles,only41%ofinfrastructuresfelttheycouldplanoverthreeyearsaheadandyetoverthreequartersofinfrastructuresarefacingmajordecisionsinthenexttwotofiveyears.

Operational issuesObtainingrobustandcomparabledataonset-upandoperationalcostsforindividualinfrastructuresischallengingastheseaccountforandattributecostsindifferentways.Giventhediversityofinfrastructures,annualoperationalandcapitalcostsrangefrom£250,000toover£4millionperinfrastructure.Themajorityofoperationalcostssupportstaff.TheaverageUK-basedinfrastructuremeets69%ofoperationalcostsfrompublicfunds,9%fromtheEuropeanUnion(EU)and22%fromothersources(e.g.businessesorcharities).

Infrastructuresmeasureandmanagetheircapacityinavarietyofways,forexampletimeavailableoninstruments,staffcapacitytooperateorprovideaccess,orstorageavailability.Forsomeinfrastructuresthatoperateasopenaccessvirtualresources,capacitycaneffectivelybeunlimited.The‘aimedcapacity’ofaninfrastructurewillfactor-intheneedformaintenanceandotherbackgroundprocessesneededtokeeptheresourceavailableforusersoverthelongerterm.

Weaskedinfrastructuresaboutthebarrierstotheireffectiveoperation.Themostfrequentlymentionedbarrierswerecertaintyoffunding andashortageofpersonnelandkeyskills(60%).Theseissueswereofteninterlinked–shorttermfundingcyclescanmakeofferinglonger-term,competitivestaffcontractsdifficult–andmanymadeparticularreferencetopersonnelshortagesindigital,datascienceandtechnicalskillsareas.

Wearegratefultoalltheinfrastructureswhichtookthetimetocompletethequestionnairesthatunderpintheanalysisinthisreport.TheimprovedunderstandingofthecharacteristicsofthelandscapewillinformUKResearchandInnovation’sfutureinfrastructureplanning. Wehavealsomadeadditionalinformation onUKinfrastructurecapabilityavailableat www.infraportal.org.uk

Top three economic sectors cited

Biologicalsciences,health&food Healthservices,agriculture,pharmaceuticals

Physicalsciences&engineering Instrumentationandelectronicsmanufacturing,energyutilities

Socialsciences,arts&humanities Creativeindustries,publicpolicyandsocialservices,communications

Environment Publicpolicy,energyutilities,agriculture

Energy Energyutilities,instrumentationandgeneralmanufacturing

E-infrastructure Computing,healthservices,communications

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Chapter 1: Introduction

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R&Dhasacentralroletoplayindrivingeconomicgrowth.MeetingtheambitionsoftheIndustrialStrategy,includingdeliveringthefourGrandChallengesandthetargettoincreasetotalR&Dinvestmentto2.4%ofGDPby2027,requiresinvestmentininfrastructureasthebasisofourresearchandinnovationlandscape1. TheabilitytodevelopnewideasanddeploythemisoneoftheUK’sgreateststrengths.TodaytheUKisgloballyrecognisedasaleaderinresearchandinnovation,havingthemostproductivesciencebaseintheG7basedonfield-weightedcitationsimpactandresearchpapersproducedperunitofR&Dexpenditure2,3. Every£1spentonpublicR&Dunlocks£1.40ofprivateR&Dinvestment4,togetherdelivering£7ofnet-economicbenefittotheUK5.Wearehighlysuccessfulintranslatingknowledgeintoreal-worldsocietal,economicandinternationalbenefit–estimatessuggestthatmorethanhalfoftheUK’sfutureproductivitygrowthwillbedrivenbytheapplicationofnewideas,researchandtechnologytocreatenewprocesses,productsandservices6.

Thesesuccessesareinlargepartfoundedon anetworkofinternationallycompetitive,high-qualityandaccessibleresearchandinnovationinfrastructure.TheUKresearchandinnovationinfrastructurelandscapeisdiverse,fromlarge-scalephysicalresearchfacilitiessuchassynchrotrons,researchshipsandscientificsatellites,tonetworksofimagingtechnologiesandknowledge-basedresourcessuchasscientific,culturalorartisticcollections,clinicalandpopulationcohorts,archives,dataandcomputingsystems.

Accesstoworld-leadinginfrastructuressupportsresearchandinnovationactivityatallscales,fromindividualinvestigatorstolargemultinationalcollaborations.Theyactasamagnettointernationaltalentandusers,contributetolocalandnationaleconomiesandgenerateknowledgeandcapabilitycriticaltoUKpolicy,securityandwell-being.ManyinfrastructureslinktothedevelopmentofkeyeconomicsectorsandSectorDealsundertheIndustrialStrategy.OthersperformvitalfunctionsforGovernmentpolicy-makersincludingstatutoryfunctions,informingpublicpolicy,improvingpublicservicesandsupporting

resilienceandresponsetoemergencies.MediainterestininfrastructuressuchastheLargeHadronCollider(LHC)atCERNinspiresandexcitesthepublicandthenextgeneration8. Suchinfrastructuresgenerateandtransferknowledgeinscienceandtechnology,trainhighlyskilledpeopleandcollaboratewithindustryasaconsumerandaprovideroftechnology9.Theyareacornerstoneoftheknowledgeeconomyandsitinthecentreoftheresearch,educationandinnovationtriangle.

AssetoutintheIndustrialStrategyGreenPaperandtheUKgovernment’sInternationalResearchandInnovationStrategy10,UKResearchandInnovationisundertakingaprogrammetounderstandtheUK’sresearchandinnovationinfrastructurecapabilitiestoguidedecision-makingandsupporttheidentificationofprioritiesto2030.Determiningthefutureneedsfirstrequiresasolidunderstandingofthecurrentinfrastructurelandscape.ThisreportprovidesapictureoftheUK’sinfrastructurelandscapein2018/19usingdatafromalmostathousandinfrastructuresandinstitutions.ItbuildsontheInitialAnalysis7oftheUK’slandscapeofinfrastructurespublishedinNovember2018andcapturesadditionalworktofillgapsinthedataandexplorekeyissuesinmoredepth.

1.1Scopeanddefinitionofresearch and innovation infrastructure

Theterm‘researchandinnovationinfrastructure’canbeinterpretedinmanyways.ForthepurposesofthisprogrammewehaveadaptedthedefinitionusedbyESFRIandtheEUFrameworkProgramme11:

Facilities,resourcesandservicesthatareused bytheresearchandinnovationcommunitiestoconductresearchandfosterinnovationintheir fields.Theyinclude:majorscientificequipment (orsetsofinstruments),knowledge-basedresourcessuchascollections,archivesandscientificdata,e-infrastructures,suchasdataandcomputingsystemsandcommunicationnetworksandany othertoolsthatareessentialtoachieveexcellence inresearchandinnovation.

Thereiscurrentlynocommonlyaccepteddefinitionof‘innovationinfrastructure’soforthisprogrammewehavefocusedon‘facilitiesandassetsthatenablethedevelopment,demonstrationanddeliveryofinnovative(new

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tomarket)products,servicesorprocessesinbusiness,publicservices,ornon-profitsectors’.Thisincludesinfrastructureaimedprimarilyatindustryandsetupexplicitlytofosterandcommercialiseinnovation,suchastheCatapultCentres,InnovationandKnowledgeCentres,CentresforAgriculturalInnovationandInnovationCentresinScotland.Italsorecognisesthewiderroleofinfrastructurewhereacademicresearchersandbusinessescollaborateandofinnovation-focusedactivitiesbasedwithinuniversities,PublicSectorResearchEstablishments(PSREs)orresearchandinnovationcampuses.

Aswithsimilarexercisesundertakeninothercountrieswearefocusingoninternational-andnational-levelinfrastructuresthatareopentoawiderangeofuserstoundertakeexcellentresearchandinnovation.Wearenotseekingtocaptureorexploreregionalorlocalneedsforinfrastructurebutrecognisetheimportanceofunderpinninginvestmentinsmallerandmid-rangefacilitieswithinuniversitiesandPSREs.Oftenfundedthroughcorecapitalbudgets,orinstitutionalorproject-specificgrants,suchequipmentandfacilitiesprovidetheessentialtoolsandfundamentalsofa‘well-found’researchestablishment.FurtherdetailsofthescopeanddefinitionaresetoutinAnnexA.

Wehavealsofocusedoninfrastructurefundedlargelythroughpublicsectorresearchandinnovationfunders.Thismeanswehavenotsoughttocapturecapabilityfundedsolelythroughprivateorcharitablemeans.However,werecognisethatpartnershipwiththethirdsectorandsharedfacilitieswithindustryandpublicservicessuchastheNHSarealsovitaltotheUKandthatmanyexistingcollaborationsandpartnershipsalreadydrawonthiscapability.Futureanalysiscoulddevelopthisthemefurther.

Wehaveconsideredinfrastructurewitharangeofprimaryfunctions,structuredunderthebroadsectorsusedbyESFRItosupportalignment ofactivities.

Biologicalsciences,healthandfood(BH&F) Physicalsciencesandengineering(PS&E) Socialsciences,artsandhumanities(SSAH) Energy(Energy)

Environment(ENV) Computationalande-infrastructure(E-INF)

However,fewinfrastructuressupportjustasinglesectorevenwhenusingdefinitionsasbroadasthesesixandwerecognisethatmostinfrastructuresservemorethanone.

1.2 Infrastructure diversityInfrastructurescomeinmanydifferentguises.Onewayofthinkingaboutthemistoconsidertheirform.Istheinfrastructurecomposedofaspecificresource–suchasacollectionofartefacts–ordoesitprovidesupportstructurestogainmeaningfromtheseresources–suchasatelescopeorhighperformancecomputer?Theresourcescanbephysical(e.g.electronmicroscope,particleaccelerator)orvirtual(e.g.datasets,digitalimages)andsomeinfrastructuresmayfallintoallthreecategories(Figure1.1).Allrequirespecialistskillsandexpertise,plusoperationalresources,suchaselectricityorcooling,tofunction.

Infrastructuresalsovarybytheiraccessmechanismandstructure.Theymaybeaccessedinperson,usedremotely,oraccessedviavirtual(digital)mechanisms.Somemayoffermultipleoptions.Forexample,anaturalhistorycollectioninamuseummayallowresearcherstohavedirectaccesstospecimens,mayofferaremoteaccessservicewherespecimensaresentoffsitetousersandmayprovidedigitisedcollectionsofthespecimensonline.

Expertise

Resources

Physical Resourcese.g. archives, samples,

collections

Facilities & Instrumentation,

Tools & Techniques

e.g. NMR, ships, data management

Virtual Resources

e.g. data sets. corpora, digitised

collections

Figure 1.1. Typesofresearchandinnovationinfrastructures.

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Manyinfrastructuresaredistributedacrossmultiplesitesandmayhaveformedfromnetworkingexistingfacilitiesorresources.Thesedistributedinfrastructuresorganiseindifferentways,e.g.usingahubandspokemodelwithaheadquartersorcoordinatinghubandmultiplespokesornodes.Someglobalinfrastructureshavemultipletierswithcontinentalandnationalnodes.Otherdistributedinfrastructureshaveequalpartnershipsratherthanahierarchicalmodel.Afewinfrastructuresclusterwithacoordinatinginfrastructureprovidingadditional,organisationalfunctions,suchastheCentreforLongitudinalStudieswiththeNationalChildDevelopmentStudy,1970,MillenniumandNextStepscohortstudies,allofwhichareinfrastructuresintheirownright.AdescriptionoftheclassificationwehaveusedinthisreportisshowninFigure1.2.

1.3ScaleandcoverageTheInitialAnalysis7oftheUK’slandscapeofinfrastructuresprovidedanearlysnapshotof ourunderstandingbasedondataprovidedthroughapproximately750in-scopequestionnairereturns.Itspublicationalsoallowedustoidentifyandfillgapsinourdata,yieldingover100additionalquestionnairereturnsandimprovingcoverageofsomesubsectors.Infrastructuresrangedinscalefromtheregionaltotheglobalandfromthoseemployingahandfulofstafftothoseemployinghundredsormore.

Toimproveourabilitytodrawconclusionsacrossthesedifferentscales,weclassifiedallquestionnairereturnsaccordingtomodeloutlinedinFigure1.2andTable1.1.Thisreportpresentsanalysesfromreturnsthatwereclassifiedaseithercoordinatinginfrastructures,infrastructuresornationalnodesofinternationalinfrastructures.Fortheoverarchingchapters(Chapters1-8)wehavefocusedoninfrastructureswithnationalorinternationalsignificance,althoughregionalinfrastructuresareincludedinsectorchapters(Chapters9-14)todevelopadeeperunderstandingoftheinfrastructurestrengthsintheseareas.

UKRI

Figure 1.2.AboveandrightDescriptionoftheorganisationalclassifications usedinthisprogramme.

Clusters (out of scope)Aclusterofinstitutionswithassociatedinfrastructures,suchasacampus, scienceparkoruniversityconsortium (e.g.theN8groupofuniversities).

Institution (out of scope)Aninstitutionwhosecorepurposeismorethantooperateasingleinfrastructure.Eithertheinstitutionhousesmultipleinfrastructuresand/oritperformssignificantotherfunctions,suchaspublicengagement.Examplesincludeuniversitiesandnationallabs.

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Coordinatinginfrastructure(inscope)Aninfrastructureinitsownrightthatcoordinatesotherinfrastructureswithinit.AnexamplecouldbetheCentreforLongitudinalStudiesthatalsohostsfourdistinctcohortinfrastructures.Itdiffersfromaninstitutioninthatitdoesnotperformsignificantotherfunctions.ManydistributedESFRIprojectsarecoordinatinginfrastructures.

Infrastructure nodes Acomponentpartofadistributedinfrastructureisanode.Nodesmaybeequalinstatureoroperateonatieredbasis.Inaninternationalinfrastructuresthereistypicallyasingleheadquartersandanumberofnationalnodesinitsmembercountriesandeachnationalnodemayhavesub-nodes (Tier2or3).Nationalinfrastructurescanhaveasimilarset-up.

(in scope) National nodes(includingtheirregionalcomponentparts)ofinternationalinfrastructureswereinscopeforthisproject,includingheadquarters.

(out of scope) Sub-nodes (Tier2or3,regionalandlocalnodes). CE

RN Im

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ASA

Cent

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dina

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Infrastructure (in scope)Facilities,resourcesandservicesthatareusedbyresearchandinnovationcommunitiestoconductresearchandfosterinnovationintheirfieldsandprovideadistinctcapability.

Infrastructurescanbephysicalorvirtualresources,orthefacilities,instruments,toolsandtechniquesthatsupportthem.Theycanbelocatedatasinglesite,mobileordistributedacrossmanyplaces.

Asingleinfrastructurecanalsobeaninstitution,e.g.Diamond(DiamondLightSourceLtd). Itwouldbecategorisedasinfrastructureifit didnotperformsignificantotherfunctions (e.g.teaching,outreach).

UKR

I

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Table 1.1.Definitionofcapabilityscalesusedinthisprogramme.Infrastructures,coordinatinginfrastructuresandnationalnodesthatwereinternationalornationalincapabilityareincludedthroughouttheanalysespresented.InfrastructuresthatareRegionalincapabilityareincludedonlyinsectorchapters(Chapters9-14).InfrastructuresthatareLocalincapabilityareoutofscopeforthisprogramme.

International

OnlycapabilityofitskindintheUK.Othersimilarcapabilitiesmayexistinothercountriesoritmaybeoneofakindglobally.Differsfromanationalinfrastructureinthatithasaninternationalreputation,withstronginternationaldraw

NationalOneofonlyahandfulofcapabilitiesintheUKortheonlyoneintheUK.Differsfromaninternationalcapabilitybybeingmorenationallyfocused,althoughitmayhavesomeinternationalusersorcollaborateinternationally

Regional InfrastructurecapabilityreplicatedintheUKataregionallevel.Itislikelytobetheonlyoneintheregion,oroneofasmallnumberintheUK

Local Infrastructureisoneofseveralsimilarcapabilitiesinaregion(regionssuchasWalesorinthesouth-eastofEngland).Outofscopeforallanalyses

1.4Questionnairemethodology,limitations and potential bias

Thisanalysisdrawsheavilyoninformationgatheredfromself-reportedquestionnaires,supplementedbyknowledgegleanedfrominterviewsandworkshops(seeAnnexBfordetailedmethodology).Questionnairesweredesignedtointeractwithexistingandplannedinfrastructuresatallstagesoftheirlifecycle.Inspring/summer2018abroad-scopeinitialquestionnaireandoptionalfocusedsecondquestionnairewereopenforcompletion.Acombinationofmethodswereusedtoidentifyandtargetinfrastructuresforthequestionnaires.Infrastructuresidentifiedviaadeskstudyandconsultationwereinviteddirectly.Also,anopenlinkwasadvertisedontheUKResearchandInnovationwebsiteanddisseminatedthroughvariousmechanisms,includingdirectengagementwithHigherEducationInstitutions(HEIs).Afteranalysisoftheseinitialtwoquestionnairesasmallnumberofkeyareaswereidentifiedtotargetinafinalwaveofengagement.Forthisfinalengagementbothquestionnaireswerecombined.

Thequestionnaireapproachallowedustogathertheinformationtosupportthelandscapeanalysisandreachabroadaudiencecompared

toalternativemethodsofinteractionsuchasinterviews.Allquestionnairesaresubjecttolimitationsandbiasanditisimportanttounderstandthesewhenreadingthisreport(seeAnnexB).GiventhatengagementwiththeUK’sinfrastructuresatthisscalehasneverbeenattemptedbefore,thedatawehaveobtainedisahealthyachievementandprovidesappropriateinformationforthisreport.However,noquestionnairewilleverengageeveryinfrastructureandthisreport,whilstbroad,cannotrepresenttheentireUKlandscape.Manyfactorsmayhaveinfluencedthequalityandquantityofinformationwewereabletogather:

Differencesinthemotivationandencouragementofdifferentgroupsofinfrastructurestoengageandcomplete ourquestionnaires

Differencesinhowentitiesinterpreted thedefinitionofaninfrastructureandindividualquestions

Completionratesforoptionalsurveyquestionsvaried

Thedataonlyrepresentasnapshotintime

Validationofself-reportedinformation islimited

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Wehavetakenstepstominimiseormitigatetheriskthatvariationinthequalityorquantityofdatawouldcauseabiasinanalysisofthelandscape.Insummarythishasincluded:

Validationofengagementcoveragebycross-referencingexistingcatalogues(e.g.ESFRI)andotherstakeholdergroups

Gap-identificationandtargetedapproachesfollowingspring/summerquestionnairecampaignstoimprovecoverage

Developmentandapplicationofacategorisationmodelfortypeandscale ofinfrastructure(Figure1.2,Table1.1)

Exclusionofquestionswheresamplesizeswerelow(e.g.optionalquestions,smallsectors)orwheretherewereconcernsoverthequalityofdataorinterpretationofthequestion.Noteveryanalysiswasdrawnfromthesamesamplesizeandnoanalysishasbeenconductedwherethesamplesizewasinsufficienttodrawconclusions

Conclusionsdrawnonlywhendemonstratedbyastrongandclearpatternindata.Noconclusionsweremadewheredifferencesweresmallorwhennotbackedupbyadditionalinsight(e.g.consultation orinterviews)

Overall,aproportionateapproachhasbeentakenwithrespecttodrawingconclusionsfromquestionnairedataandtheanalysishasbeenusedtosupportothersourcesofunderstandingratherthanreplacethem.

Furtherdetailsarepresentedin AnnexB:Methodology.

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Chapter 2: Overview of the landscape

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TheUKhasarichanddiverselandscapeofresearchandinnovationinfrastructureswithover750thatreportatleastaregionalsignificance.Therewere945individualresponsestothequestionnairesintotal(excludingduplicateresponses).Forthepurposesoffurtheranalysis,afterverifyingthequalityandcompletenessofthequestionnaires,thedatasetwasrestrictedtothosethatwecategorisedaseither:

Infrastructures Coordinatinginfrastructures,or Nationalnodesofinternationalinfrastructures

andwereatleastregionallyornationally/internationallysignificant.Ofthese,224wereregionallysignificantand527werenationallyorinternationallysignificant.Theseformthedatasetsusedforsubsequentquantitativeanalysisinthisreport.ForChapters2-8discussionsarelimitedtothe527infrastructuresofnationalorinternationalsignificance.Thesectorchapters(Chapters9-14)drawonthebroadersampleof751infrastructuresofregionalsignificanceorgreatertoenableamoredetailedunderstandingoftheseareas.

Thereareanumberofreasonswhy194questionnaireresponseswereexcludedfromquantitativeanalyses.Justoveraquarterrepresentedcollectionsofinfrastructuresatagreaterscalethanourcriteria,suchasacampusoraninstitution,wheredataforfunctionsotherthaninfrastructureswereincludedandinseparable.Forexample,aresponseforanentiremuseummayincludecostandstaffingdataforoutreachpurposesandauniversitydepartmentmaydosoforteaching.Wherepossiblethesecontributorswerere-approachedforclarificationandifnecessarytoprovidedatafortheirinfrastructuresseparately.

Ifnewdatawerenotreceived,appropriateinsightfromthesequestionnairesabouttheinfrastructuresthemselveswasincludedfordescriptivepurposesbuttheirdatadonotappearintheanalysespresented.Justoverathirdofexcludedquestionnaireresponseswerefrominfrastructuresatasmallerscalethancoveredbytheroadmapprogramme,suchasthosecoveringsmallpiecesofequipmentoralocalnodeofanationalinfrastructure.Therestfailedothercriteriachecks,suchasprovidingaccesstoindividualsfromoutsidethehostinstitution,orwereincompleteresponses.

Thereasonsbehindtheexclusionsareshown inFigure2.1.

InfrastructuresarelocatedinallregionsoftheUK.Thequestionnaireidentifiedafurtherforty-seveninfrastructureslocatedoutsideoftheUKinatleasttwenty-fivedifferentcountriesthatprovidedprivilegedUKaccess,e.g.throughUKfundingormembershippartnerships.As84%ofinfrastructuresarehousedwithinotherinstitutions,primarilyHEIs,thepatternofinfrastructuredistributionwithintheUKfollowsthegeneralpatternofnationalresearchandinnovationfunding.

1%

25%

34%7%

33%Clusters

Institutions

Local infrastructures

Partial response

Failed other criteria

1%

25%

34%7%

33%Clusters

Institutions

Local infrastructures

Partial response

Failed other criteria

Figure 2.1.Reasonsbehindtheexclusionofquestionnaireresponsesforquantitativeanalysis.

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2.1 The cross-disciplinary nature of infrastructures

Researchandinnovationinfrastructuresoccurbothwithinandacrosssectorborders.Eachsectorisdifferentbothinsizeandinmanyofitscharacteristics.Infrastructureswereaskedtoselecttheprimarysectortheyidentifiedwith(Figure2.2).Thephysicalsciencesandengineeringandbiologicalsciences,healthandfoodsectorshadthelargestproportionofinfrastructuresthatidentifiedthemastheirprimarysector(29%and26%ofthetotalrespondents),aswouldbepredictedbythebroadcoverageofthesesectordomains.

Thesmallestnumberofresponsescamefromthesectorswithanarrowerormoredefinedscope,energyandcomputationalande-infrastructure.Thesetwosectorshadpreviouslyconductedstudiestoidentifyalloftheinfrastructureswithinthem.Thisquestionnairereachedmostofthesewithin thecomputationalande-infrastructuresectorandoverhalfwithintheenergysector.

Researchandinnovationisrarelycontainedwithinasingledomain.Ninety-twopercentofinfrastructuresworkedacrossmorethanonesector(mean=3.7sectors,median=4sectors,i.e.threesectorsinadditiontotheirprimarydomain).Thenumberofsectorsengagedwithvarieddependingonprimarysector(Figure2.3).Infrastructuresinthecomputationalande-infrastructuresectorhadthebroadestreach,with78%identifyingwiththreeormoreadditionalsectorsand45%identifyingwitheverysector,whichreflectsthepervasiveroleofmanysuche-infrastructures.Theenvironmentsectorhadthenextbroadestreachwithoverthreequartersidentifyingthisastheirprimarysectoralsoidentifyingwiththreeormoreadditionalsectors.Fifteenpercentofinfrastructurescoveredallsixsectors.

26%

29%13%

6%

16%

10%

BH&F

PS&E

SSAH

Energy

ENV

E-INF

26%

29%13%

6%

16%

10%

BH&F

PS&E

SSAH

Energy

ENV

E-INF

Figure 2.2.Distributionofresearchandinnovationinfrastructuresaccordingtotheprimarysectortheyidentifiedwith.

0% 20% 40% 60% 80% 100%

BH&F

PS&E

SSAH

ENV

Energy

E-INF

All

1

2

3

4

5

6

Figure 2.3.Numberofsectorsthatinfrastructuresfromthedifferentsectorsengagedwith.

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Case study: UK’s national ore collection greens the search for scarce resources

TheNaturalHistoryMuseum’sorecollectionholdsmorethan15,000specimensfromacrosstheglobeandisoneoftheworld’sforemostmineraldepositscollections.Usingthisreferencelibraryofthedifferentphysicalandchemicalpropertiesofores,museumscientistsandcuratorshelpnaturalresourcecompaniesreducethecostandecologicalfootprintofexplorationfornewmetaldeposits,developmoreenvironmentallysustainableprocessingtechnologiesandtraingeosciencestudentsandprofessionals.

Themuseumissimilarlyhelpingoptimisetherecoveryofe-techmetalslikerare-earthelementsandindiumandidentifynewsourcesandextractiontechniquesforlithiumandcobalt,increasinglyusedinlightweight,rechargeablebatteriesthatpowerportabletechnologiesandelectricvehicles.InadditionanewmultidisciplinaryinitiativebetweenlifeandEarthscientistsiscurrentlyexamininghowtheinteractionbetweenorganismsandmineralsinsoilsatcontaminatedsitesmightbeharnessedtodevelopbetterstrategiesfortherehabilitationofformerminesites.

Theorecollection,whichhasbeendevelopedthroughmuseumscientists’fieldworkoverthepast200yearsanddonations,formspartoftheeighty-million-strongnaturalsciencespecimensheldbythemuseum,thenationalcollection.ItisanimportantresourceforscientistsintheUKandglobally.Themuseum’scollectionincludesspecimensfromexpeditionstotheChileanAndes’Maipovalley,toshedlighton theformationofcopperdeposits.

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2.2Large-scale,multi-sectorfacilitiesTheUKsupportsaccesstoanumberoflarge-scalefacilitiesthatareestablishedwiththeintentiontoserveawidemultitudeofsectors,bothintheUKandoverseas.TheUKhasastrongtrackrecordinestablishingandoperatingsuchfacilities.Theyoftenoperateformanydecades,takemanyyearsofplanningandaretechnicallycomplexnecessitatingdeliverythroughnational-andinternational-scalecollaborations(Figure2.4).Theyaredesignedtosupportusersfromacrossacademiaandbusinesssectorswithskilledtechnicalstaff

workingcloselywithvisitingresearchers.Cross-fertilisationofideasisstimulatedatsuchfacilitieswhereusersbringavarietyofresearchquestionsandinnovationchallenges.Thesefacilitiesarededicatedtocharacterisingandimagingthemolecularandatomicstructuresofinorganicandbiologicalmaterialsusingarangeoftechniquessuchassynchrotrons,conventionalandfree-electronlasers(FELs),X-rays,neutronreactorsorspallationsources.Theyhaveapplicationsinareasasdiverseascleanenergyandtheenvironment,drugdesign,advancedengineeringandelectronics.

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TheUKisapartnerinmanyinternationallarge-scale,multi-sectorfacilitiesincludingtheInstitutMaxvonLaue–PaulLangevin(ILL),EuropeanSpallationSource(ESS),EuropeanX-rayFree-ElectronLaserFacility(EU-XFEL)andEuropeanSynchrotronRadiationFacility(ESRF).UK-basedlarge-scalefacilitiesarebasedattheRutherfordAppletonLaboratory(RAL)ontheHarwellCampus.TheseincludetheDiamondLightSource,theCentralLaserFacility(CLF)andtheISISNeutronandMuonSource.Thisco-locationatHarwellallowscross-fertilisationofideasthatcanleadtonewproducts,servicesandbusinessopportunities.Thesefacilitiessupportresearchandinnovationacrosssectors.TheconnectiontothewiderresearchandinnovationbaseareenhancedbycomplementarysupportfacilitiesincludingtheResearchComplexatHarwell(RCaH).RCaHhousesCLFlasers,imagingequipmentandsamplepreparationsuitesforsampleshavingshortlifetimesorthatcannottravelgreatdistances.

TheUKisinvolvedinthedevelopmentofalarge-scale,multi-sectorfacilitythatisbeingconstructedinSweden,theEuropeanSpallationSource(ESS).Itsroleinitsconstructionincludesanumberof‘inkind’contributionsoftechnologydevelopedwithUKpartnersandindustry,therebybuildingtheUK’sskillsbaseandcontributingtotheUK’slocaleconomy.Thetechnologywillformpartoftheaccelerator,theneutron-scatteringsystemsandthetargetsystems.ESSwillbetheworld’smostpowerfulneutronsourceandwillprovidenewopportunitiesforresearchersinabroadrangeofscientificareasincludinglifesciences,energy,environmentaltechnology,culturalheritageandfundamentalphysicsandcomplementthecapabilityofournationalneutronfacility,ISIS.

1970 >2030

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Figure 2.4.Timelinesoflargescalemulti-sectorinfrastructures.

Case study: The European Synchrotron Radiation Facility (ESRF)

ESRFinGrenobleistheworld’smostintenseX-raysource.Nearly9,000scientistsfromaroundtheworldvisitthefacilityeveryyeartoconductexperimentsinfieldsincludinglifesciences,chemistry,materialphysics,culturalheritageandenvironmentalsciences.Industrialapplicationsincludepharmaceuticals,engineering,nanotechnologiesandsemiconductors.

ThirtyyearsagotheESRFwastheworld’sfirstthird-generationsynchrotronandsincethenithascontributedtoover30,000publicationsandthreeNobelPrizes.ThefacilitycontinuestorevolutionisesynchrotronsciencewiththedesignandconstructionoftheExtremelyBrilliantSourceupgradethatwillbetheworld’sfirstfourth-generationsynchrotronwhenthefacilityreopenstousersin2020.

ESRF

Health services.Incancer,somereceptorsare‘hijacked’todrivetumourformation. Inpersonalisedcancertherapy,drugsblocktheseroguereceptors,deprivingthecancercellsofvitalsignallinginstructionsanddirectingthemtowarddestruction.Targeting SlitproteinsandRoboreceptorshaslongbeenconsideredapromisingtherapeuticapproachfortypesofpancreatic,skinandbreastcancer.However,andalmostcertainlyduetoaninsufficientstructuralandmechanisticunderstandingofRoboactivationandsignalling,therearecurrentlynoRobo-directeddrugs.UsingtheESRFithasbeenpossibletogaininformationnecessarytodesigneffectivedrugstargetingRoboreceptors.Inparticular,ithasrevealedmolecularsitesthat,whentargetedbydesigneddrugs,will allowustomanipulateactivationandinhibitioninpatients,providingnewpossibilities forcancertreatments12.

Manufacturingpharmaceuticals.Agroupofhumanproteinsknownas‘G-proteincoupledreceptors’playsanimportantroleinvariousdiseasesincludingdiabetes,osteoporosis,obesity,cancer,neurodegeneration,cardiovasculardisease,headachesandpsychiatricdisorders.Thismakesthemexcellentdrugtargets.However,theyarenotalwayseasytostudy.Scientistsfromclinical-stagecompany,HeptaresTherapeutics,areusingDiamond tolearnmoreaboutthesereceptorsandhowwecanusethemtodesignbetter,moreeffectivemedicines13.

Agriculture.Thewaxsurfaceontheleavesofplants,suchasbarleyandwheatcrops,actsasaprotectivebarrieragainstenvironmentalattacksincludingpestsandwater/nutrientlossandisparamountforthewellbeingandsurvivalofallplants.ScientistsattheUniversityofManchesterhavegeneratedamodelofthewaxsurfaceofleavessimilartothoseofwheatandbarleycrops,tobetterunderstandhowpesticidesmodifythesebarriers.TheteamconductedneutronreflectometrystudiesattheILLandISISfacilitiestoexaminetheprocessesofwateruptakeinthewaxfilmspresentonthesurfaceofplants.Thisisthefirsttimeanyonehasusedextractedwaxestorecreatethewaxshieldthatplantsuseforprotection.Asaresult,thenewtoolenablesscientiststostudyhowpesticidesenterplantsbycrossingthewaxbarrieronleaves.Itisanothersteptowardsfine-tuningthechemicalsusedinagriculturetomaximisecropyieldswithoutdamagingtheplants14.

Energy.WorkingwiththeOpenUniversity,EDFEnergysaved£3billionbyextendingthelifeofnuclearpowerstationsbyfiveyears.ISISwasusedtopredictthelifetimeofweldsandtheknowledgegainedenabledlifeextensionstofifteennuclearreactors.Benefitsincludedprovidinglow-carbonenergytotwomillionhomes,£650millionayearincontractsformostlyUK-basedbusinessestocarryouttherepairworkandthesafeguardingof2000jobsinthenuclearpowerindustry.

Transport (aeronautic).Alotofresearchgoesintocreatingaircraftthatdeliverpassengersandcargosafelyandefficiently.UsingDiamond,scientistsfromRolls-Roycehavestudiedtheimpactofastrengtheningsurfacetreatmentappliedtoaeroplanefanblades.Exploringthemicrostructuralimpactofstressonthefanbladegivesusvitalinformationtoinformfutureaircraftdesign13.

Security. SpatiallyoffsetRamanSpectroscopy,atechniquedevelopedandpatentedattheCLFprovidesamethodforidentifyingthechemicalcompositionunderneaththesurfaceofmaterials,includingbeneaththeskinandliquidsinbottleswithoutcuttingthemopen.ThetechnologywascommercialisedthroughthespinoutcompanyCobaltLightSystems,whichhassincebeenacquiredbyAgilent.Thelaser-basedsystemsareusedcommerciallytodetectexplosivesinairportsacrosstheworld,keepingpeoplesaferandonthemove.

Someexamplesofthesocio-economicoutputsfromlarge-scalemulti-sectorfacilities:

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Chapter 3: Lifecycle

Natural History Museum

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PlanningIdentifying the need and developing the case for a new infrastructure.

PreparationRefinement of technical

design including preliminary scoping of prototype studies to help reduce risk and cost

of financial construction. During this time, development

of governance, definition of legal status and financial

sustainability may take place.

OperationInfrastructure is fully

operational. During this time, regular review and

upgrades may take place to keep the infrastructure at

the cutting edge.

ConstructionPhysical construction of the new infrastructure, establishing the network for virtual and/or distributed infrastructure.

Decommissioning or repurposingAt the end of its lifecycle an infrastructure will either be shut down or may evolve to take on new functions in response to changing demand and technology.

This can be a complex process, involving careful data management, or additional funding and skills to manage any transition, environment or safety issues.

3.1 ConceptArecognisedconceptofthelifecycleofaninfrastructure15,16,hasbeenadoptedforthepurposesofthisprogramme.Thelifecyclestagesofaninfrastructurefollowthepathofplanning,preparation,construction,operationanddecommissioningorrepurposing(Figure3.1).Therelevanceordefinitionofthesestagescanvarywiththenatureoftheinfrastructureandsectoritserves.Forexample,foralarge

physicalinfrastructuretheconstructionphasewouldencompassbuildingandcommissioningequipment.However,foradistributedinfrastructurethestagemightrefertotheestablishmentofaheadquartersordevelopmentofanetworkofdistributedresources.Movementbetweenthestagesisnotalwaysclearlydefinedandcanbeafluidprocesswithsomestagesrunninginparalleloroverlapping.

Figure 3.1.Stagesofaninfrastructure’slifecycle.

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3.2 Current lifecycle landscapeThereisacurrentlandscapeofestablishedandoperationalinfrastructuresintheUK,with82%reportingthattheywereattheoperationalstage.Overall,18%ofinfrastructureswereinearlylifecyclestages(development,designorimplementation).Onlyoneinfrastructureidentifiedasbeinginthedecommissioning/repurposingstageandreportedthatthecapabilitywasbeingreplacedbyfundinga freshentity.

TherehasbeenasteadygrowthinthenumberofUKinfrastructures,withmorenewinfrastructuresoperatingsince2010thaninanyotherdecade(Figure3.2).Thiscouldbedrivenbyanumberoffactors.Itcouldreflectagrowthinthenumberofinfrastructuresfollowingtheinjectionofcapitalfundinginthepastdecadeinresponsetotheincreasingimportanceofinfrastructuresforsolvingchallengesandunderpinningresearchandinnovation.Theremightbeahigherlevelofresponsivenessfromnewinfrastructuresthat,bytheverynatureof

obtainingfunding,haverecentengagementwithfunders.Somesectorsseedafieldinresponsetoanewchallengeareabyfundingavarietyofprojectsintheexpectationthat,duetothenatureofthefield,onlysomewillconsolidateandbetakenforwardinthelongerterm.Wewillalsohavemissedcapturingthoseinfrastructuresthatbeganandendedoperationspriortothisprogramme.

Sixtypercentofinfrastructureshadexpectedoperationallifespansofovertwenty-fiveyears(Figure3.3).Therearedifferencesbetweensectors.Withinthecomputationalande-infrastructuresectorwherethetechnologyusedhasafastturnoverrate,42%ofinfrastructureshaveanexpectedoperationallifespanofovertwenty-fiveyears,whereasthreequartersormoreofinfrastructuresinthesocialsciences,artsandhumanitiesandenvironmentsectorsexpecttooperateforovertwenty-fiveyears.Theseincludecollectionsanddatasetsthatincreaseinvalueovertime.

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Figure 3.3. Sectordifferencesintheexpectedoperatinglifespansofinfrastructures.

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Case study: Research infrastructure for heritage science

IPERIONCHestablishedacross-disciplinarynetworkofovertwentypartnersfromtheUK,EuropeandtheUSA.Itconnectedresearchersinthehumanitiesandnaturalsciencesandprovidedaccesstoexpertise,instruments,methodologiesanddataforadvancingknowledgeandinnovationintheconservationandrestorationofculturalheritage.Theconsortiumbroughttogethermajorcentresofresearchinheritagescience,includingoutstandingresearchinstitutes,aswellasprestigiousresearchlaboratoriesandconservationcentresinbothmuseumsanduniversities.

NetworkingactivitiespromotedinnovationthroughtechnologytransferanddynamicinvolvementofSMEs,improvedaccessproceduresbysettingupacoordinatedandintegratedapproachforharmonisingandenhancinginteroperabilityamongthefacilitiesandidentifiedfuturescientificchallenges,bestpracticesandprotocolsformeasurementsandoptimisedtheuseofdigitaltoolsinheritagescience.IPERIONCHdeliveredsocialandculturalinnovationbytraininganewgenerationofresearchersandprofessionals,byinnovationofresearchinstrumentsandmethodsandbyworldwidedisseminationandcommunicationtodiverseaudiences.

IPERIONCHledtotheestablishmentofadistributedEuropeanResearchInfrastructureforHeritageScience(E-RIHS),whichhasbeenpartoftheESFRIroadmapsince2016.TheUKnodeofE-RIHS,UKResearchInfrastructureforHeritageScience,isadistributedinfrastructureonitsown,withovertwentyinstitutionalpartnersaswellasarangeofresearchcapabilities,includinguniversities,museums,heritageorganisations,digitalinfrastructuresandlaboratoryfacilities(suchasDiamond).Themissionoftheinternationalinfrastructureistostretchtheboundariesandtheimpactofheritagesciencebydevelopingthemostcomprehensiveandadvancedscientificandtechnologicalcapabilities.Itwillenableresearchers,organisationsandindustrytodevelopskills,knowledgeandinnovationtoenabletheappreciationandpreservationofheritageandtodrivecross-disciplinaryapplicationsofheritagescience.

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Figure 3.4.Evolutionoftypesofinfrastructures.

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3.3 Evolution of the landscapeTherehasbeenasteadyevolutionofthetypesofinfrastructuresestablished(Figure3.4).Theearliestinfrastructurestendedtobecollectionshousedinmuseums,librariesorgardens.Afterthatinfrastructuresrespondedtothesocialandpoliticaldriversofthetime,forexampletheincreasedneedforfood,withthefirstagriculturalandenvironmentalinfrastructuresappearingearlyinthetwentiethcentury.The1950s,1960sand1970ssawtheestablishmentofsomeofthelargeorganisationalinfrastructuressuchasatCERN,theESO,SanfordandtheBritishLibraryandalsotheinitiationoflong-termcohortsanddatasets.Thediversityofinfrastructuredisciplineareasalsobegantogrow.Bythe1980slargecomputeanddatainfrastructureswereestablished.Throughthe1990sand2000sdiversitycontinuedtoexplode.Infrastructureswereestablishedintopicalareasofresearchandinnovation;termssuchasneuroimaging,autonomoussystemsandgeneticswerefirstseen,atrendthatcontinuedintothe2010swithmanymentionsof‘omics’,quantumande-infrastructure.

3.4LifecycleandplanningTheexpectedoperationallifecycleofinfrastructuresvariesaccordingtotheorganisationalandlegalmodeloftheinfrastructure(Figure3.5).Infrastructuresestablishedaslegalentities(nationalandinternational)havelongerexpectedlifespansthanthosehousedinotherinstitutions.Infrastructuresreliantonshort-termfundingarelesslikelytohaveanoperationallifespanofovertwenty-fiveyearsthaninfrastructuresinotherorganisationalandlegalstructures.

Despitetheirlonglifespans,overthreequartersofinfrastructuresstatedthattheyarefacingmajordecisionpointsinthenextfiveyearsandfor74%oftheseitfallswithinthenexttwoyears.Justunderhalfofallinfrastructuresreportedthattheywillfacetwoofthesemajordecisionsinthenextfiveyearsandforhalfofthesebothdecisionsaredueinthenexttwoyears.Only41%ofrespondentsfeelthattheyareabletoplanbeyondthreeyearsahead,highlightingamismatchbetweenfundingcyclesforresearchandinnovationinfrastructureandplanningrequirements.

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Figure 3.5. Percentageofinfrastructureswithexpectedoperationallifespansfromuptofiveyearstomorethantwenty-fiveyears,groupedaccordingtotheirlegalorganisationalstructure.

Thetypesofdecisionthatinfrastructuresfacefellintosixbroadcategories:

1. Financial: afundingrevieworperformanceassessmentaspartofamid-grantassessmentorplannedreviewcycle

2. Financial:fundinghasended–usually duetotheendofgrantfundingandtheinfrastructureseekingrenewaltocontinue

3. Financial:significantfinancialchangesarebeingconsideredsuchasachangeinfinancialmodel,seekingnewincomesourcesorone-offstrategicdecisionsthatrequirefinancialsupportsuchasanupgradeorshifttooperationalfundingpostset-up

4. Financial:theresponsemakesspecificreferencetoanEUrelatedfundingdecision

5. Strategic:amajorstrategicdecisionthatwillhaveafundamentalimpactontheoverallmissionandpurposeoftheinfrastructure

6. Strategic:astrategicchoiceaboutoperationsorashiftinlifecyclestage

Thereareoverlapsbetweenstrategicchoicesandmajorfinancialdecisionsonallocations,basedonthedescriptionofsituationsgivenintheresponses.Justoverathirdwerestrategicinnature,relatedeithertochangesintheoverallmissionoftheinfrastructure(forexample,resultingfromapolicyrevieworrespondingtouserdemand)ortothefacingofmajorchoicesabouttheiroperations(oftenrelatedtobuildinglocation)andtransitiontodifferentlifecyclestages.Twothirdsofdecisionswerefinancialinnature,mostlyrelatedtotheenddateofexistingfundingandtheneedtoapplyfornewfundingtocontinueoperationsortheneedtoseekadditionalfundingandincome(e.g.forupgradesorchangesinoperationalmodelsuchasthetransitiontobecomingself-financing postset-up).

ThereisaneedforcontinuedeffortinunderstandingthelifecycleoftheUKinfrastructurelandscapeoverallandatsectorlevel.Byunderstandingitsdynamicsandevolution,itsmainfeaturesandchallenges,theUKwillbeevenbetterequippedtoplanitsfuturelandscapeinawaythatisrealistic,sustainableandagile(andthereforecapableofrespondingtonewdevelopments)andisholisticinitsapproachtosustainability.

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Chapter 4: International collaboration and cooperation

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TheSmithReviewdemonstratestheimportanceofinternationalcollaboration.Sharedinfrastructuresareinherentlycollaborativeandpromoteinternationalcooperation,interdisciplinaryresearch,innovationandskillstraining.Byassemblingacriticalmassofpeople,knowledgeandinvestment,sharedinfrastructurescancontributetosignificantregionalandnationaleconomicdevelopment,attractingtalent,industrialengagementandinwardinvestment.TheresearchandinnovationinfrastructurecommunitiescontributeheavilytotheUK’sglobalstatusinR&D.

4.1 International collaborationNinety-fivepercentofallinfrastructurescollaborateintheirwork.Mostinfrastructuresthatcollaboratedosowithinternationalpartners(91%),withonly9%havingnational-onlycollaborations.Wheninfrastructureswereaskedtoself-identifytheirscopeorreach,83%ofallinfrastructuresfelttheyhadaninternationalscope,whichisindicativeoftheinternationalnatureoftheresearchtheyconductaswellasoftheiraspirationsandpositioningintheglobalcontext.Almostallinfrastructure(97%)inthesocialsciences,artsandhumanitiessector self-identifiedwithhavinganinternational scopeorreach.

Infrastructuresareoftensharedand/orusedbyresearchersandinnovatorsfromdifferentcountries,offeringcostefficienciesaswellasaccesstoabroadrangeoffacilitiesthatotherwisewouldnotbeaffordable.Insome

fields,infrastructuresaresoexpensivetobuildandoperatethattheircostscanbebeyondtheresourcesofasinglecountry.Anotherdriverforcollaborationcomesfromthechallengesandthreatsfacingsocietytoday,whichoftendonotrecognisenationalboundariesandrequireacollaborativeapproachtotackle.

Fromthe527questionnaireresponses,204wereclassifiedasinternational.Theyweredistributedacrossthesixsectorsinasimilarpatterntotheoverallnumbersofinfrastructures,withproportionallyslightlymoreintheenvironmentandPS&Esectors(Figure4.1).Physicalsciencesandengineeringinternationalinfrastructuresarecharacterisedbyhavingmoreoftheverylarge,expensivephysicalinfrastructuresthatarebeyondofthescopeofasinglecountrytodeliver,e.g.particleacceleratorsandtelescopes.

4.2.StaffingResearchandinnovationinfrastructuresarekeyplayershelpingmobilisetalentacrosstheworld,enrichingthepooloftechnicalskills,trainingthenextgenerationofresearchersandstimulatingthemobilityofleadersandindoingthistheycontributetoaccelerateadvancesinresearchandtechnology.InfrastructuresbasedintheUKattractsignificanttalentfromaroundtheworld,where27%ofstaffcomefromoutsidetheUK,morethantheHEIsectorasawhole(20%)(Figure4.2).Infrastructuresinthecomputationalande-infrastructuresectoraremostreliantonnon-UKstaff(39%).

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Figure 4.2. NationalityofstaffemployedatUKinfrastructures(outercircle)andHEIs(innercircle);sourceHigherEducationStatisticalAgency(HESA)staffdata201717(academicandnon-academic).

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Figure 4.3.AttractionofUK-basedinfrastructurestointernationalusersbasedontheir primarysector.

Figure 4.4.Reasonscitedbyinfrastructuresforattractinginternationalusers.Notethatoptionswerenotmutuallyexclusiveandparticipantscouldselectallthatwererelevant.

4.3 International user baseIntheinfrastructurelandscapethereisaconstantflowofusersseekingaccesstothebestfacilities,wherevertheyare.IntheUK39%ofindividualusersofinfrastructurescomefromoutsidetheUKand91%ofinfrastructureshaveaninternationaluserbase(Figure4.3).Almostallinfrastructures(95%)considerthattherewillbeachangeindemandbytheuser-baseinthenearfuture.Forty-sixpercentofthemthinkthebalancewillremainsimilartotoday,40%think itwillbeincreasinglyinternationallybiased andonly14%thinktherewillbeagreater nationalfocus.

ThereasonswhyUK-basedinfrastructuresattractusersfromoverseasarevaried(Figure4.4).Oftenitwasreportedtobebecausenosimilarcapabilityexistselsewhere,itbeinganintegralpartofaninternationalcollaboration, orbecauseitofferedanoverall‘package’ (e.g.asupportpackageoraccesstocomplementaryfacilities)significantly betterthanthatofferedbyothers.

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Infrastructuresareinherentlyinternational.Wecollaboratebecausemanyoftheresearchandinnovationchallengesthatinfrastructuresarehelpingtosolveareglobalintheirnature,suchaschangingoceantemperaturesormovingvastquantitiesofdataaroundtheplanet.SomeinfrastructurescanonlybesitedincertainlocationsoutsideoftheUK,suchastheremote,radio-quietregionsorcloud-freeskiesrequiredforastronomyfacilities.Infrastructurescanalsobeverycostly,beyondthebudgetsofasinglenation. TheSKAwillbetheworld’slargestandmostsensitiveradiotelescopearray.Whilstthetenmembercountries,includingtheUK,arethecornerstoneoftheproject,therearearound100organisationsfromaround20countriesparticipatingintheoveralldesignanddevelopment.

SKA Organisation

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Chapter 5: Skills and Staffing

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Researchandinnovationinfrastructuresofallsizesrequirestaffwithhighlyspecialisedskillstomaximisethepotentialutilityoftheinfrastructure,fromthemanagersoftheseinfrastructurestothetechniciansthatoperatethemdaily.Havingtheseskillsinplacenotonlyrealisesthedaytodayfunctionofaninfrastructurebutalsocontributestotheinnovationofnewtechnologiesandtechniquesanddisseminationofgoodpractices.Tocaptureasnapshotofskillsandstaffinthecurrentinfrastructurelandscape,respondentswereaskedtoanswerquestionsonstaffnumbers,sex,ethnicityblack,Asianandminorityethnicbackgrounds(BAME)andstaffroles.WhereappropriatethestaffingofinfrastructureshasbeencomparedtostaffingacrossUKHEIsaccordingtoHESA2017data17combinedforacademicandnon-academicstaff.

5.1 Numbers StaffnumbersweremeasuredasthenumberofFTEstocontrolforvariationinworkingpatterns.The480nationalandinternationalinfrastructureslocatedwithintheUKemployjustunder25,000FTEs.ThenumberofFTEsemployedbyeachsectorintheUKfollowsasimilarpatternasthenumberofinfrastructuresineachsectorbutwithSSAHandBH&FemployingthemoststaffandPS&Ehavingfewerthantheirsharewouldpredict(Figure5.1).However,manylargePS&EinfrastructuresareinternationalfacilitiesoutsideoftheUKandthusexcludedfromthisfinding.ThemediannumberofstaffworkingateachUK-based

infrastructureistenFTEs,rangingfromthreeFTEsintheenvironmentsectortotwelveFTEsinBH&F.

Acrossallinfrastructuresregardlessoflocation,infrastructuresthataresetupastheirownlegalentitytendedtoemploysignificantlyhighernumbersofstaffthaninfrastructuresthatwerehousedinotherlegalentities(Figure5.2).Thispatternispartlydrivenbyarelativelysmallnumberofverylargeandofteninternationalinfrastructurestypicalofthisfield,suchastheLHCatCERN,ESOandtheHighValueManufacturingCatapult.Itisalsolikelythatinternationally-hostedinfrastructuresmayhaveunderestimatedstaffnumbersduetothedifficultyofattributingstaffworkingacrossinfrastructuresandotheractivities.

Infrastructuresthatwerethenationalnodeofaninternationalinfrastructurehadalowerheadcountthanthosecategorisedasanentireinfrastructure(Figure5.3).Thisrelatestoanationalnodebeingasubsetoftheinfrastructure’scapability.Coordinatinginfrastructures,thosethatwereconsideredaninfrastructureintheirownrightbutincludedotherinfrastructures(suchassomeESFRIs),hadthegreatestnumberofstaff.Similarly,staffnumbersincreasedfromthoseinfrastructuresprovidingaregionalcapability,toanationalcapability,toaninternationalcapabilitywhenconsideringthefulldatasetof751infrastructures(Figure5.4).

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Figure 5.1.Staffnumbers(FTEs)employedatinfrastructuresineachofthesixsectors(restrictedtoinfrastructureslocatedintheUK).

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Figure 5.4.Meanstaffnumbers(FTEs)atinfrastructurescategorisedasprovidingaregional,nationalorinternationalcapability.Thisresultusedthedatasetof751questionnaireresponsestoincludethoseofregionalcapability.

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Infrastructuresneedarangeofskillstooperate.Onaverage,38%ofstaffareemployedintechnicalroles,33%areinresearchrolesand29%performotherfunctionssuchasmanagement,administrationandoutreach.

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5.2 RolesInfrastructuresdependonthefunctioningofarangeofdifferentrolesthatcanbebroadlycategorisedasresearch,technicalorother(e.g.management,administration).Fiveofthesixsectorshadmorethanthree-quartersoftheirstaffperformingresearchandtechnicalroles(Figure5.5).Thesocialsciences,artsandhumanitiessectorhas69%ofstafflistedasbeingin‘otherroles’,whichincludeslargeESFRIinfrastructuresaswellasmuseums,archivesandcollections.TechnicalrolesareespeciallyprevalentintheenvironmentandPS&Esectors,makinguparoundhalfofallroles.

5.3 Staff diversityInfrastructuresemployproportionallyfewerfemalesandasimilarproportionofstaffwithBAMEethnicitycomparedtoHEIsintheUK(Figure5.6).

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80%

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Research Technical Other

Figure 5.5. Staffrolesininfrastructures.Onaverage,33%ofstaffemployedbyinfrastructuresfillresearchroles,38%technicalrolesand29%otherroles.

BAME

White

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Infras

Female

Male

HEIs

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Female

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InfrasFigure 5.6. ProportionofstaffemployedatUKinfrastructures(outercircle)andHEIs(innercircle)accordingto(a)ethnicityand(b)sex.ProportionallymorestaffemployedatinfrastructuresaremalecomparedtostaffatHEIs(61%versus46%).ThepercentagesofstaffofBAMEethnicityaresimilarforinfrastructuresandHEIs(14%versus13%)(HESAstaffdata201717).

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Case study: The role of infrastructures in the provision of skills and training

TheUniversityofSheffieldAdvancedManufacturingResearchCentre(AMRC)isanetworkofworld-leadingresearchandinnovationcentresworkingwithadvancedmanufacturingcompaniesaroundtheglobe,specialisingincarryingoutresearchintoadvancedmachining,manufacturingandmaterials,whichisofpracticalusetoindustry.

Itemploysover500highlyqualifiedresearchandtechnicalprofessionalsfromaroundtheglobe.Theresearchinfrastructurealsooffersrolesinmanagementandadministration.TheAMRCTrainingCentreoperatesanApprenticeTrainingProgrammethathas250-300positionsperyear.Theprogrammestructureincludesatwo-yearbasicapprenticeship,atwo-yearhigherapprenticeshipandafoundationdegree.AspartoftheUniversityofSheffieldtheapprenticescanthenprogresstoHonours,Masters,EngDandPhDlevels.FortheyoungpeopleintheSheffieldCityRegion,itprovidesthefoundationforarewardingcareerinsomeoftheworld’smostinnovativeindustries.

TheAMRCalsooffersgraduateandMScprogrammesforengineers.Aspartoftheprogrammegraduatesstudyforapostgraduatediplomainengineeringmanagement,whichisaimedatengineerswhowanttomoveintomanagementwhilemaintainingtheircompetenciesintechnicalsubjects.Furthertothis,theIndustrialDoctorateCentre(IDC)offersgraduatestheopportunitytolearnandearninfour-yearengineeringdoctorateprogrammes,whichcombinetaughtmoduleswithoriginalresearchforworld-leadingengineeringcompanies.RecentengineeringdoctorateprogrammesincludeadvancedprojectsforRolls-RoyceandTechnicut.

AMRC

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Chapter 6: Operations

39

Obtainingrobustandcomparabledataontheset-upandongoingcostsforinfrastructuresischallenginggiventhediversityofactivityandbusinessmodelswithintheUKlandscape.Theinfrastructurequestionnairesaskedrespondentstoprovidetheapproximatecostsofestablishingtheirinfrastructureandthecostsofrunningiteveryyear,thoughresponserateswereonly33%-48%acrossthesequestions.

Aswellasvaryingbysubjectareaandtype ofresearch,costsdependonarangeofoperationalandfinancialmanagementissues.Theseinclude:

Theapproachtocalculatingandaccountingforoverheadswhenaninfrastructureispartofalargerorganisation

Howcommoncostsaresharedbetweeninfrastructuresornodesofadistributedinfrastructure

Howcostsaresharedbetweenco-funders(includinginternationalpartners)

Thetreatmentofdepreciationof capitalequipment

Thelegalstatusofaninfrastructureandapproachtomanagingfluctuationinspendovertime

Respondentsalsovariedintheirapproachtoaccountingforstaffcosts,usuallyreflectingtheirfundingmodel.Forexample,thecostoftheoperationalstaffrequiredtorunaninfrastructurewasusuallyincludedbuttheresearchstaffmaynothavebeenifaseparatefundersupportsprojectsusingthatinfrastructure.Infrastructuremanagersthemselvesmayalsonotbefullyawareofhowtheirhostorganisationattributesandmanagesoverheadcostsandthiswilllikelyvaryfromorganisationtoorganisation.Ingeneralthismeansthefigurespresentedherearelikelytobeanunderestimateofthefulloperationalexpenditureassociatedwithindividualinfrastructures.

Despitethesechallengessomebroadobservationscanbemadebasedonthedataavailable.Figure6.1showsthediversityin

annualoperatingandcapitalcostsacrossthequestionnaireresponses.Foraboutoneinfiveinfrastructurestheannualcostofoperations(excludingcapitalequipment)islessthan£250,000,whilstasimilarproportion(18%)haveanannualoperationalcostof£4millionormore.Theannualcostofcapital,includingprovision,maintenance,replacementorupgrades,alsovariessignificantlyacrossinfrastructures.Thespikeof49%ofinfrastructureshavingcapitalcostsbelow£250,000isreflectiveofnon-capital-intensiveinfrastructures,e.g.someinfrastructuresintheSSAHsector.

Giventhatthebulkofoperationalcostisoftenforstaffsalaries,thereisastrongcorrelationbetweenoperationalcostsandfull-timeequivalentstaffnumbers(correlationcoefficient=0.81).Figure6.2showsthescatterplotforthoseinfrastructureswithlessthan100staffandwithannualoperationalcostsof£4.5millionorless.Thelineofbestfitdisplaysthepositiveassociationbetweenthetwovariables.

Infrastructuresthatareshort-termfundedprojects(e.g.theUKMultipleSclerosisRegister,alargecohortstudy)typicallyhavelowerannualcoststhaninfrastructuresthatareeithernationalorinternationallegalentities(e.g.theNationalCompositesCentre).Someshort-termfundedprojectsarelong-termactivitiessurvivingbetweensustainablefundingoptions.Thosehousedinotherentitiesmayhavetheircostsunder-reportedbecauseofoverheadsharingorattribution.Long-terminfrastructureslocatedininstitutionshaveafairlyuniformspreadacrossthecostcategories,whereasthoseoperatingasalegalentityweremorelikelytohavecostsinthehighercategories(Figure6.3).

6.1 Set-up capital costsManyinfrastructuresrequireasignificantup-frontinvestmentincapitalequipment.Ofthoseinfrastructuresestablishedsince2010thatprovideddataonthecapitalcostassociatedwithsettingup,abouthalfhadacapitalcostrequirementof£6millionormore(Figure6.4).Almostoneintenrequired£62millionormore,withinternationalinfrastructuressuchastheESSrequiringmorethan£1billion.

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Infrastructure set-up capital cost (£ million)

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<250k 250k - <500k 500k - <1m 1m - <2m 2m - <4m ≥4m

Average operational cost per year (£)

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Figure 6.1.Distributionofaverage,annualoperationalandcapitalcostestimatesforinfrastructures (k=thousand, m=million).

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<250k 250k - <500k 500k - <1m 1m - <2m 2m - <4m ≥4m

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National/international legal entity

Figure 6.2. Scatterplotofinfrastructuresshowingstaffnumbersplottedagainstaverage,annualoperationalcosts(onlyinfrastructureswithfewerthan100staffandannualoperationalcostsof£4.5millionorlessshown,thoughthepositiveassociationremainstrueforallinfrastructures).

Figure 6.3. Distributionofinfrastructures’totalannualcostsbasedontheirlegalmodel (k=£thousand, m=£million).

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6.2SourcesoffundingThisprogrammefocusesonresearchandinnovationinfrastructureswitharelianceonpublicsourcesoffundingforestablishmentand/oroperations.Thismeanswehaveexcludedfromouranalysisanyinfrastructuresthatstatedtheydidnotrelyonpublicfunds,althoughwerecognisethatthereareimportantcomponentsoftheUK’soverallcapabilitythatarefundedthroughcharitableandprivatemeans.

ThefinaldatasetconfirmsthepatternsdescribedintheInitialAnalysis7.Thereisagreatrelianceonpublicfundingtosetupaninfrastructure,whichcontinuesforoperationalcostswithroughlyhalfofrespondentsreliantonpublicfundingtocovermorethan70%ofthecostoftheiroperations(Figure6.5).Thisislikely

tobeanunderestimationbecausethreequartersofrespondentsarebasedininstitutionssuchasHEIsorPSREsandarereliantontheirhostorganisationforaproportionoftheircosts(seeabove).Thismakesattributionoffundingsourcemorechallengingtoquantifyprecisely.

OperatingcostsarefundedmostlythroughUKsourcesofpublicfunding–theaveragenationalinfrastructurecovers73%ofitsoperatingcostswithUKpublicfunds(Figure6.6).EUfundingmeets7%oftheoperatingcostsofnationalinfrastructuresand15%ofinternationalinfrastructures.Itistargetedtowardtheearlystagesofinfrastructures’lifecycles–bringingnetworkstogether,planningandpreparation.TheEUdoesnotfundsignificantoperationalcostsbutitdoesfundaccessandopening

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≤10% 11–30% 31–70% 71–90% >90%

% reliance on funding from UK public sources

Establishment Operations

Figure 6.4. Distribution ofinfrastructure set-upcapital cost(infrastructuresestablished since2010).

Figure 6.5. Degreeofrelianceonpublicfundingfortheestablishmentandoperationsofinfrastructures.

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73%

7%

20%

59%

15%

26%

UK public sources

EU funding sources

Other

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6%

3%

56%

11%

9%

Government department

Innovate UK

Arms-length body

Research Council

Devolved Administration funder

Other

InternationalinfrastructuresNationalinfrastructures

Figure 6.6.Sourcesoffundingfortheoperationalcostsofinfrastructures. Figure 6.7. Primarysourceofpublicfundingforinfrastructures.

59%

15%

26%

UK public sources

EU funding sources

Other

16%

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9%


Innovate UK

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Innovate UK

Arms-length body

Research Council


Other

upinfrastructurestointernationalusersandreleasingtheinnovationpotentialofoperatinginfrastructures.Wherefurtherinformationwasgivenaboutthe‘other’sourcesofoperationalfunding,thiswassplitbetweencommercialactivitytogenerateincome,industryandcharitablefundingforprojects,donationsandphilanthropicsources,internationalresearchorganisationfunding(oftenviausersfromthosecountriestravellingtoaccessUKinfrastructures)andsomelocalauthorityfunding.Industryfundingwasthemostprevalentaccountingfor47%ofthe‘other’sources.

6.3PrimaryfundingsourceTheprimarypublicfundingsourcewasoverwhelminglytheResearchCouncils(Figure6.7),covering56%ofinfrastructures.TherelianceontheResearchCouncilsincreasedto62%whenconsideringonlythoseinfrastructuresmostdependentonpublicfundingfortheiroverallcosts(i.e.reliantfor>70%ofestablishmentcosts).ThisreflectstheResearchCouncils’roleinsupportingthetypesofunderpinninginfrastructureconsideredinthisreportandtheeaseofattributionoffundingthroughgrantsawardeddirectlytoaninfrastructure.Theremaining44%recordtheirprimarypublicfunderaseitherInnovateUK,agovernmentdepartment,anarms-lengthpublicbodyorDevolvedAdministrationfunder.Thegovernmentsourcesmostfrequentlymentioned

aseitheraprimaryfunderoracontributorweretheDepartmentforBusiness,EnergyandIndustrialStrategy(BEIS),theDepartmentforDigital,Culture,MediaandSport(DCMS),theDepartmentofHealth&SocialCare(DHSC),theDepartmentforEnvironment,FoodandRuralAffairs(Defra)andlocalsources(alocalenterprisepartnershiporalocalauthority).Withinthe‘other’categorymanyreceivefundingfrommultiplesources,includingEUfundingstreamsandcharitablesourcesalongsidefundingfromResearchCouncilsorauniversity.

Theroleofresearchcapitalfundingprovideddirectlytouniversitiesthroughdevolvedfunders(theScottishFundingCouncil,HigherEducationFundingCouncilforWales,DepartmentforEmploymentandLearningNorthernIrelandandHigherEducationFundingCouncilforEngland,nowResearchEngland)iscomplex18,19,andlikelytobeunder-reported.Somerespondentsreportedoracknowledgedthisfundingstream.However,othersthatwerehostedwithinuniversitiesdidnotincluderesearchcapitalfundingintheirfundingsources.Itislikelythatmanyofthesedobenefitfromthisdevolvedfunding,althoughthepreciselevelofsupportwillbesubjecttohowfundsaremanagedwithinindividualuniversities.Universitiesreceiveincomefrommultiplesourcesanditwasnotpossibletoexplorethepreciseallocationof suchfundsthroughthisquestionnaire.

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Chapter 7: Measuring usage and capacity

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7.1UsageMeasuringusageandcapacityiscomplexgiventhediversityofinfrastructuresandrangeofaccessmodels.Infrastructuresthathavephysicalresourcesorprovidefacilitiesandequipmentoftenrecordtheaccessofindividualsorgroups,ormaycountthenumberofexperimentsperformed.Thereareusuallyupperlimitsonthenumberofusersthattheycansupport,e.g.timelimitedequipmentusage,oraccesstoacollectionlimitedbytheavailabilityofanexpertabletointerpretthatcollection.Suchinfrastructurescanbethoughtofashavingtheircapacitycappedinsomeway.Ontheotherhand,somevirtualinfrastructurescanoperateopenaccessmodelsandmayonlybelimitedbythebandwidthoftheirnetworkorcomputerarchitectures.Ratherthancountindividuals,groupsorexperiments,theseinfrastructuresmayreportusagebythenumberofdownloadsperformedandmayhavemillionsof‘users’.Theseinfrastructurescanbethoughtofashavinganuncappedcapacity.Nearlythreequartersofinfrastructureshavetheircapacitycappedinsomewayand12%areuncapped(Figure7.1).

Theapproachtomeasuringusagevarieswidelybysector.Infrastructuresintheenvironment,computationalande-infrastructureandBH&Fsectorsreportedthattheymadegreateruseofvirtualaccessmechanisms.Theseareasoftendeveloporprovideaccesstolargedatasets.TheaveragenumberofdownloadsperyearwithintheSSAHandBH&Fsectorswasinthe85,000to110,000range,butfortheenvironmentandcomputationalande-infrastructuresectorsitwasaround200,000,000downloadsperannumandrepresentedover99%of‘users’.ThePS&Eandenergysectorsconverselydidnothaveinfrastructureswhereusersweremeasuredbydownloadsorothervirtualmeans.

Allsectorshadinfrastructuresprovidingphysicalaccesstousersrecordedaseitherindividualresearchers,researchgroupsornumbersofexperiments(Figure7.2).Infrastructuresaveraged200-5400individualusersperinfrastructureperannuminallsectorsexceptforSSAH,whichrecordedsignificantlygreaternumbers.Thisisdrivenbyfootfallanddigitalaccesstoarchives,museums,librariesandothercollections.

72%

12%

16%

Capped

Uncapped

Did not answer

Figure 7.1.Percentageofinfrastructuresthathavetheircapacitycappedinsomeway(e.g.timeonequipment)comparedtothosethathaveuncappedcapacity(e.g.openaccessdatadownloads).

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BH&F PS&E SSAH ENV Energy E-INF All

Individuals Groups Experiments Downloads/hits Other

Figure 7.2.Percentageofinfrastructuresineachsectorthatmeasureusage accordingtoeitherindividuals/groups,experimentsperformed,downloads/hitoranothermeasure.

72%

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16%

Capped

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Did not answer

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7.2MeasuringcapacityAninfrastructure’sapproachtocapacitymeasurementisdependentonwhattheyaresetuptodo.Itcanbefocusedonmeasuresofoutputor,incaseswherethisisdifficult,theabilitytodeliverproductsorservices.Unlimitedusagecanoftenbemadeofvirtualresources,suchasdatasets.

Thevaryingapproachestocapacitymeasurementdescribedinresponsestoourquestionnaireshavebeengroupedintosevenbroadcategories:

Output capacity: howmuchtheinfrastructureproduces,e.g.samplesprocessed,surveysconducted,dataproduced

Operating/instrument/experimenttime(hours,days,weeks):the‘up-time’of theinfrastructure

Numberofusers/experiments:thenumberofusers/experimentsthatcanbeservedorfacilitated

Space/equipment/resourceavailability: theamountofthecapabilitiesneededbyresearchers/innovatorsthattheinfrastructurecanprovide

Staff availability:thenumberofstaff, orstafftime

Computingpower:specificfore-infrastructure

Onlineresources/collections/data:capacitycannotbemeasuredandnearunlimitedusecanbemadeoftheinfrastructure

Thesecategoriesarenotmutuallyexclusiveandmanyinfrastructurestalkedabouttheircapacityinmultipleways;forexample,operatingtimeandstaffavailabilitycouldbepairedduetomachinesbeingunusablewithoutkeystaff.Figure7.3showsthepercentageofinfrastructuresineachsectorthatdescribedtheircapacityaccordingtotheabovecategories.Thepercentageofinfrastructuresthatdidnotanswerthequestionisalsoshown.Whilstthequestionwasoptionalandsomenon-responsewasexpected,non-responsewasalsodrivenbycapacitymeasurementbeinglessmeaningfulforcertaininfrastructures,includingthosewithnoconstraintsonuse(e.g.someopenaccessonlineresources).

Differencesinsectorresponsesaboutmeasuresofcapacityareindicativeofthetypesofinfrastructureineachsector.Infrastructuresintheenergy,PS&Eorenvironmentsectorscommonlyspokeaboutcapacityintermsofoperating/instrument/experimenttime.About30%ofBH&Finfrastructuresmentionedstaffavailabilitywhendescribingcapacity.Arelativelyhighpercentageofcomputationalande-infrastructuresmentionedspace/equipment/resourceavailability,whichispartiallyrelatedtovirtualstoragespace,alongsidemeasuresofcomputingpower.About30%ofoperationalSSAHinfrastructuresdidnotanswerthequestionaroundcapacitymeasurement,whichcouldreflectthechallengeofseparatingvisitornumbersforengagementpurposeswiththoseforresearchpurposes(e.g.inamuseumorlibrary),orthatfootfallisnotmeasured.

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Figure 7.3.Howinfrastructuresmeasurecapacity.Someinfrastructuresdescribedcapacityinmultipleways,sopercentagesdonotsumto100%.

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7.3ManagingcapacityAlmostnoinfrastructurecanrunat100%capacityfor100%ofthetime.Weaskedinfrastructurestodescribetheiraimedcapacitylevels,i.e.theleveltheyaimtorunat.Aimedcapacitycanbethoughtofasapercentageofthemaximumtheoreticalcapacityoftheinfrastructure.Thetheoreticalmaximumcapacityisnotalwaysfeasibleordesiredparticularlywhenconsideringinfrastructuremanagementoveralongtimeperiod.Manyinfrastructuresrequireblocksofdowntimeformaintenanceorupgrades(e.g.anengineeringfacility)ormustalwaysrunnon-outputprocessesinthebackground(e.g.monitoringandaccountingprocessesrunningonahighperformancecomputing(HPC)machine).

Sparecapacitycanbethoughtofasthedifferencebetweenaimedcapacityandthelevelthataninfrastructureisrunningat.Forexample,afacilitymayaimtorunfor200daysperyear.Ifitaveragesrunningfor137daysayear,itssparecapacitywouldbe63/200daysor31.5%.Ouranalysisofsparecapacityhassomecaveatsassparecapacitycanbedifficulttomeasure.Statisticsalsomayhavebeeninflatedbymisinterpretationofthedifferentcapacitymeasuresaskedforintheinfrastructurequestionnaire.

Weexaminedthe157infrastructuresthatbeganoperatingbefore2016whichprovidedfiguresforcapacity.Overhalfofthesewereoperatingattheiraimedcapacityandjustunderhalfhadsomesparecapacity.Thelikelihoodofhavingsparecapacityvariedaccordingtohowcapacitywasmeasuredandbysector(Figure7.4).Forexample,59%ofinfrastructuresthatmeasuredcapacityby‘up-time’hadsparecapacity,whilst29%ofinfrastructuresthatusedstaffingasameasuredid.

0% 10% 20% 30% 40% 50% 60% 70%

Operating instrument/experiment time

Space/equipment/resource availability

Number of users/experiments

Output capacity

Staff availability

Computing power

Figure 7.4. Percentageofinfrastructureswithsparecapacitybasedoncapacitymeasure.

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Case study: The Large Hadron Collider

TheLHCatCERNistheworld’slargestandmostpowerfulparticleaccelerator.Tokeeptheacceleratoroperatingsafely,effectivelyandreliably,itisshutdownoverthewintermonthsformaintenanceandupgrades.Furthermore,everyfourtofiveyearstheacceleratorexperiencesalongshutdownthatcanlastovertwoyears.TheseshutdownsareessentialforensuringtheLHCoperatesatitsoptimumandisdevelopedtocontinuouslysupportground-breakingscience.

ThecaseoftheLHCdemonstratesthetrade-offbetweenmakingfulluseofaninfrastructureintheshortrunandsustainingandmaximisingitspotentialinthelongrun.Forgoodreasonsmanyinfrastructuresdonotaimtooperateallofthetime.

CERN

Therearemanypossiblereasonsforsparecapacity.Infrastructuresthatareoperationalbutstilldeveloping(e.g.addingnewcapabilities)maybeinaramping-upphase.Itcantaketimeforinfrastructurestoincreaseoperationallevelstoaimedcapacityorfullyexploitnewresources.Evidenceforsparecapacityduetorampingupincludesalmosttwiceasmanyinfrastructuresoperatingsince2012havingsparecapacitycomparedtoolderinfrastructures.Additionally,75%ofinfrastructureswithsparecapacityobservedincreaseddemandforphysicalaccesswithinthelasttenyears.

Sparecapacitycanalsobeduetogenuinelackofdemand,forexampleifthereisover-supply.Asinfrastructuresage,technologicaladvancesandtheemergenceofsubstituteinfrastructurescouldcausedemandtodecrease.Inthesecaseswewouldexpecttoseeadeclineindemandalongsidereportsofsparecapacity.Overall,onlyfiveofthe157infrastructures(3%)withsparecapacityreportedthatdemandfortheirinfrastructurehaddeclinedwithinthelast tenyears.

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Case study: The Material and Chemical Characterisation facility (MC2)

MC2attheUniversityofBathincorporatesservicesfornuclearmagneticresonance(NMR),massspectrometry,X-raydiffraction,thermal/elemental/surfaceanalysis,dynamicreactionmonitoring,electronmicroscopy,bio-imagingandcellanalysis,onscalesrangingfromthemoleculartotheorganismlevel.Theinfrastructuremeasurescapacityintermsofaccessiblehoursofoperationandaimstooperateat75%capacity(variablebyinstrument).Theremaining25%ofinstrumenttimeissetasideforinstrumentset-up,methoddevelopment,maintenance,staff/usertrainingandoutreachactivities.

WhilstMC2aimstooperateatanaverageof75%capacityacrossalloftheinstrumentation,itwilloperatebelowthisforsome.Thelevelofusevariesmarkedlybetweeninstruments,dependingonitspurpose,withsomeinstrumentsoperatingoptimallyat30%capacityallowingfornear-real-timeaccessandanalysis,e.g.openaccessNMRsystems,whilstotherinstrumentsareusedat~90%capacityforexperimentswhichcanbescheduledseveralmonthsinadvance.Thisemphasisesimportantreasonsforsparecapacity–theavailabilitytoaccommodateurgentwork,aswellasamoreresponsiveserviceforthecommunityofuserswhereneeded,e.g.inreactionmonitoring.

7.4 Barriers to performanceThemajorityofthebarrierstoperformanceidentifiedwerecommonacrossallsectors.Figure7.5clustersresponsesunderthemainthemes.Themostfrequentlymentionedconcernswerearoundfundingfollowedbyshortagesofpersonnelandshortageofkeyskills,whichwereofteninterlinked.Retentionofkeypeople,particularlydigital/data/technicalskill-setswasarecurringbarrier.Manyrespondentslinkedthistotheshort-termnatureoffunding,meaningitwasonlypossibletooffershort-termcontracts,whicharelessattractivewhenmorecompetitivesalariesareavailableintheprivatesector.

Fundingissues.Inadditiontocommentsontheleveloffunding,manyresponsesflaggedtheshort-termnatureoffunding,andtheuncertaintythisbrings,asacriticalbarrierwithimplicationsforoperationandstaffrecruitment/retention.Otherscitedtheneedfor‘batteriestobeincluded’andwereconcernedaboutthecomplexityofthelandscape.Someweregrapplingwiththerecentchangestothefundinglandscapeandhowtoreacttodifferentfundingstructures.Manyraisedconcernsabouttheimplications

ofexitingtheEUexitforfunding– particularlythoseininternationally significantinfrastructures

Personnelandskillsshortages.Oftentiedtoneedsforoperationalfunding,therewerenotablementionsofashortageofdatascienceandanalyticalskillsandsoftwareengineersacrossresponses,regardlessofsector.Thechallengeofshort-termcontractswasalsomentioned

Datarelatedchallenges.Themostfrequentlyraisedissuewasthatofaccesstoandsharingofdata

Managingcomplexpartnerships.Thistendedtobecitedmostlybythoseinvolvedinmulti-countryormulti-funderinfrastructures

Other barriersreferencedincludedarangeofoperationalortechnicalissuesspecifictothetypeofinfrastructure,challengesassociatedwithinter-andmultidisciplinaryworking,governmentcontrolsandregulatorybarriers,competitionwithotherinfrastructures(includingprivatesector)andarangeofculturalissueswithinorganisations,withinacademiaorlinkingtobusiness

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Respondentswerealsoaskedabouthowthesebarriersmightchangeoverthemid-term.Responseswerelargelythesamewithstabilityoffunding(includingworriesovertheshort-term,unpredictablenatureoffunding)andstaffing-relatedissuescitedmostfrequently.However,theemphasisshiftedslightlywithgreatermentionsofbuildingcapabilitywithintheinfrastructure,includingbarrierstostaffsuccessionplanning(attraction/retentionconcerns),worriesaboutmaintainingexcellenceinthefaceofcompetition(internationally,fromotherinfrastructuresandtheprivatesector),abilitytobuildtheusercommunityandhowtoincreasecapacitytoengagebusinessusers.

Therewerealsoincreasedmentionsofuncertaintyoverhowtheeconomywillevolve,impactofnewtechnologiesandhowtheresearchenvironmentitselfwillchangewitha‘lackofstrategy’asaconcern.Issuesrelatingtothemanagementanduseofdatacontinuedtoberaisedbutwithagreateremphasisonpotentialfuturerestrictionstoaccess,standardsandpublictrust.

Infrastructuresalsoindicatedhowtheyweremitigatingtheserisks.Thisincluded:

Seekingtodiversifyfundingstreams

Arangeofstrategiestomanagesuccessionproblems,toincreasetheattractivenessofrolesandbringyoungtalentintotheinfrastructures.Theseoftenfocusedoncontinuousprogrammesofrecruitment,useofapprenticeships,seekingbetterrecognitionoftechnicalstaffanddevelopmentofothernon-payoffers

Puttingresourceintointernalandexternallyavailabletrainingprogrammes

Activelyseekingtoworkwitharangeofpartnerstoformcollaborationsandsharerisks,costsandtechnical/capacitychallenges(i.e.academicandprivatecollaborations)

Proactiveworktoraiseawarenessoftheinfrastructurecapabilityandsupportgrowthofusercommunities

Engagementwithgovernmentandotherpartiesinrelationtobroaderconcernsbeyondtheremitoftheinfrastructure,suchasdataaccessregulation

27%

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8%

8%

7%

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Personnel shortage

Skills/knowledge shortage

Data-related challenges

Technical or operational barriers

Uncertaintity around EU exit (funding,staff, collaborations)Government policy uncertainty orregulatory issuesCapacity to meet demand

Age of equipment

Managing complex partnerships/ engagingnew partnersOther

Figure 7.5. Barriersandconcernscitedbyinfrastructures.

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Managing complex partnerships/ engagingnew partnersOther

Case study: Foundries, a fertile training ground

Oneofthehallmarksofthesyntheticbiologycommunityhasbeenitsdrivetowardsgreaterdemocracyamongbothparticipantsandbeneficiaries.Thisextendstoskillsandtrainingbutwhilstweareaddressingthegapatgraduatelevelandbeyond,thereremainsapressingshortageofappropriatelytrainedtechnicians.

NationalfacilitiessuchasEdinburgh’sGenomeFoundry,oneofthelargestautomatedgenomeassemblyplatformsintheUK,areaninvaluabletraininggroundforearly-careerresearchersinstate-of-the-arttechniques.Alongsidethedevelopmentanddeliveryofawidevarietyofgenomeassemblyprojects–fromnaturalproductbiosynthesistogenetherapy–thefoundryhashostedmanyguests,frombothacademicandindustriallabs,allkeentobetterunderstandtheroleofautomationinsyntheticbiology.

TheUKCentreforMammalianSyntheticBiology,basedattheUniversityofEdinburgh,hasstartedtoaddressthegapinentry-levelskillsandtechniciansbyhiringschool-leaversasmodernapprenticesinitsspecialistresearchfacilities.TheapprenticesworkinthelabwhilegainingformalqualificationsasalabtechnicianthroughdayreleasetoFifeCollege.Aftercompletinghistraining,thecentre’sfirstapprentice,ScottNeilson,beganworkintheEdinburghGenomeFoundry.Therehehasbecomeindispensable,acquiring‘greenfingers’inoperatingandmaintainingthehighlysophisticatedplatformforDNAassembly.ScottiscurrentlyworkingtowardsaHigherNationalDiplomaandpotentially,inthefuture,apart-timedegree.Hehasalsoprovedtobeanadeptinstructorandshareshisnewly-gainedexpertisewithfoundrycustomers.

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Chapter 8: Links to the economy

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8.1WorkingwithbusinessesOverthreequartersofinfrastructuresreportedthattheyconductedsomeworkwithUKbusinessesand18%statedthatallormostworkwasdirectlywithUKbusinesses(Figure8.1).Theenergy,PS&Eandcomputationalande-infrastructuresectorsreportedthehighestfiguresforengagement.However,theinterpretationofthequestionmayhavevariedbysector.IntheSSAHsectorworkingwithbusinessesintheclassicalsenseislesscommonbutworkingwithgovernmenttoinformpublicpolicyiscommon(applyingto75%ofinfrastructures).

Athirdofinfrastructureshaveabalancedportfolioofactivitiesacrossdiscoveryandcommercialisationresearch(Figure8.2). Acrosssectors,energyhadthegreatestproportionofitsworkcommerciallyfocused(25%),considerablyabovetheothersectors,whichrangedfrom3-10%.

Theknowledgeandinnovationrolesofinfrastructuresmakeimportantcontributionsacrosstheeconomy.WeaskedinfrastructurestoselecttheeconomicsectorsthattheycontributetofromalistoffortyeconomicsectorcategoriesbasedongroupedStandardIndustrialClassificationdivisions20(seeAnnexBfordetails).ResearchandeducationwerethetopsectorsidentifiedwhichistobeexpectedgiventheirroleingeneratingnewknowledgeandtheirassociationwithHEIs.ThetoptenothereconomicsectorsselectedareshowninTable8.1.Twenty-eighteconomicsectorswereselectedbyeightyormoreinfrastructures,andallofthefortyeconomicsectorcategorieswereeachidentifiedbyatleastfifteeninfrastructures,demonstratingthebroadeconomicandsocietalimpactgeneratedbyinfrastructures.

0%

10%

20%

30%

40%

50%

BH&F PS&E SSAH Energy ENV E-INF AllMostly discovery More discovery Balanced More commercialisation

Figure 8.2. Workatinfrastructuresonadiscovery-to-commercialisationspectrum.

0%

10%

20%

30%

40%

50%

60%

70%

80%

All work Most work Some work Not at all

BH&F PS&E SSAH Energy ENV E-INF

Figure 8.1. ExtenttowhichinfrastructuresworkwithUKbusinesses.

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Figure 8.3. Top10economicsectorsthatresearchandinnovationinfrastructureseethemselvescontributingtoorworkingwith(excludingresearchandeducation).

Researchandinnovationinfrastructureslocatedincloseproximitycanhavehada‘clustering’effect,fosteringinnovationandincreasinglinkswithindustry.ExamplesofaninfrastructureclustercouldincludeacampussuchastheBabrahamResearchcampus,auniversityconsortiumsuchastheN8researchpartnership,orascienceparksuchasCulhamScienceParkwhichhostsCulhamCentreforFusionEnergy.

Clustersaroundresearchandinnovationinfrastructurescanhavemanybenefits,includingtothelocaleconomy,increasedskillsandjobstoaregionandattractingtalentforacademiaandindustry.Aclustercancreatean‘innovationecosystem’withinaregion,thusacceleratingthedevelopmentoftechnology andthecommercialisationofprojects.

Case study: Proximity to drive innovation: the Cambridge Biomedical Campus

TheCambridgeBiomedicalCampusbringstogetherworld-leadingdiscoverysciencealongsideinfrastructures,clinicalresearch,teachinghospitalsandpharmaceuticalandbiotechnologycompaniestocreateavibrantclinicalresearchcommunityattheforefrontofdiscoveryscienceandmedicine.Thiscampusprovidesanunparalleledpatient-centredapproachtoresearchbyworkingalongsideNHSandclinicalscientistsandpartnerstoeffectivelyplanandmanageclinicaltrials.

Theinitialcampusdatesto1962whenthenewAddenbrooke’sHospitalandtheMedicalResearchCouncil(MRC)LaboratoryforMolecularBiology(LMB)relocated.Anewvisiontobuildapatient-centricresearchcommunitycomprisingacademics,cliniciansandbusinesswasannouncedin1999.Thefirstphaseexpandedthecampustohouse,amongothers,theglobalheadquartersforAstraZeneca,theUniversityofCambridgeSchoolofClinicalMedicineandthenewLMBbuildingwhichopenedin2013.TheLMBhasmaderevolutionarycontributionstosciencesuchaspioneeringthesequencingofDNAandthedevelopmentofmonoclonalantibodies.TwelveNobelPrizeshavebeenawardedforworkcarriedoutbyLMBscientists.

Clusteringinfrastructureswithclinicalfacilities,businessesandresearchandinnovationinstitutionsbringspeopletogethertoaccelerateinnovationaswellasprovidingaccesstotechnologyplatformsandequipment.Thisinnovativeenvironmentsupportsteaching,discoveryresearch,patientcareandcommercialR&Dincloseproximity,allowingideastobediscussedandprogressedandsuccessfulresultstobetranslatedintotangiblebenefitsforpatientsmoreefficiently.

Health Services182 (38%)

Energy Utilities161 (34%)

Instrumentation Manufacturing

156 (33%)

Computing & Data Services

140 (29%)

Public Policy198 (42%)

PharmaceuticalsManufacturing

134 (28%)

Electronic Manufacturing

112 (24%)

Agriculture151 (32%)

Communications & information143 (30%)

Aeronautical Transportation

106 (22%)

Case study: V&A collections inspire the development of sustainable fibres

TheBusinessofFashion,TextilesandTechnologyCreativeR&DPartnershipisoneofnineclusters(plusonepolicyandevidencecentre)tobefundedunderthemulti-millionpoundCreativeIndustriesClustersProgramme.LedbyLondonCollegeofFashion,UniversityoftheArtsLondon,thefive-yearprojectwillfocusondeliveringinnovationwithintheentirefashionandtextilesupplychain,withspecialattentiongiventopositioningindustryasagentsofnewtechnologyandmaterialsdevelopment.

DrawingontheV&A’srichcollectionofhistoricaltextilesanddress,V&AcuratorsandtextilesconservatorswillbeworkingwithcolleaguesfromLondonCollegeofFashion,UniversityoftheArtsLondon,andtheSchoolofDesign,LeedsUniversityononeparticularproject.Thisprojectwillusenineteenthcenturydyebooks,recipes,recordsoftheanimalandwasteproductcollections,historicalfibresandtextilesasastartingpointfordevelopingnew,sustainablysourcedandproducedfibresandcompositematerials.

ArecentexhibitionattheV&AentitledFashionedfromNaturefocusedonproductionmethodsandrawmaterials,aswellastheireffectoncommunitiesandthenaturalenvironment.Itshowcasedexamplesofpioneering‘alternativefibres’manufacturedinEuropeinthenineteenthandearlytwentiethcentury,usingmaterialssuchasspunglass,pineappleleaffibreandotherorganicandwastematerials,whichmightprovidepointerstocreatingamoresustainablefashionindustrytoday.

Theaimofthisprogramme21istofosteranew,creativebusinesscultureinwhichfashion,textileandtechnologyenterprises,fromSMEstomultinationalcompanies,canuseR&Dasaroutetogrowth.Specialattentionwillbeplacedonpositioningindustryasagentsofresearchanddevelopmentintonewmaterials,technologyandsustainablebusinesspractices.

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Chapter 9: Biological sciences, health and food sector

Gerd Altmann from Pixabay

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Researchandinnovationinthebiologicalsciences,healthandfoodsectorusesanarrayofworld-classinfrastructuresandcapabilitiestounderstandthecomplexitiesofform,functionandinteractionswithinandbetweenorganismsandtotranslatethesediscoveriesforsocietalandeconomicbenefit.Thelifesciencescommunityexploresfundamentalscientificquestionsbyutilisingcomplexexperimentalapproachesthatgeneratevastamountsofdata,oftenfromhigh-throughputapproachesandbyapplyingthesedatafortheimprovementofhealth,agriculture,theenvironmentandsocietyatlarge.Asthecomplexityofapproacheshasincreasedandadvancesintechnologyhaveaccelerated,sohastheneedtoworkwithinandacrosstraditionaldisciplinaryboundaries.Scientistsacrossdifferentfields,fromclinicianstoengineersandfrombiologiststosocialscientists,areconvergingtosolvethepresentandfutureproblemstowhichoursocietyis,orwillbe,exposed.

WithintheUK,therearemanystakeholderssupportingthedeliveryoflifescienceresearch.WithinUKResearchandInnovationmuchofthisiscoveredbytheremitsoftheBiotechnologyandBiologicalSciencesResearchCouncil(BBSRC)andtheMRC.Inaddition,thisareaissupportedbyotherpublicsectororganisations,industryandthethirdsector,including:

TheNHSandotherhealth-relatedgovernmentalbodies (e.g.PublicHealthEngland)

DevolvedAdministrations(e.g.NorthernIrelandinvestsheavilyinfoodsafety, Scotlandinanimalphenotyping,Walesinagricultureandimaging)

ClinicalinfrastructuressupportedbyUKhealthdepartments,forexampletheNationalInstituteforHealthResearch(NIHR)22 fundedthroughtheDHSC

Biomedicalresearchcharities23

Industrial/commercialpartnerswhosupportinnovationandresearch(e.g.Syngenta)

Farmsandagriculturalnetworks(e.g.TheRoslinInstitutecollaborateswithfarmerstoperformresearch/collectdataontheirland)

TheUKiswellconnectedwithEuropeaninfrastructuresandisapartnerinsixofthesixteenHealthandFoodResearchInfrastructuressupportedbyESFRI24 .

9.1 Current landscapeInfrastructuresintheBH&Fsectorincludedatabanks,biologicaltissuebanksandothercollectionsofbiologicalsamples,integratedclustersofsmallresearchfacilities,high-capacity/throughputtechnology,high-costcutting-edgeanalyticalinfrastructure,high-fidelityimagingtechnology,facilitiesforanimalandplanthousing,breedingandphenotyping,networksofcomputinginfrastructures,databasesandresearchcohortsofvolunteers.Ofthe751infrastructureswitharegional,nationalorinternationalscope,244reportedtheirprimarydomainastheBH&Fsector.Inaddition,53%ofotherrespondentshighlightedthattheirinfrastructureshadrelevantlinkstotheBH&Fsector(Figure9.1).Thishighleveloflinkageemphasisestheengagementandinvolvementofscientistsfromthephysical,engineering,computational,mathematicalandsocialsciencesintacklingresearchchallengesacrossthelifesciencescommunityandtheimportanceofchallengesinthelifesciencesformingpartoftheaimsofawiderangeofinfrastructures.

Accordingly,thesuiteofinfrastructuresintheBH&Fsectorarediverseinnatureandarecomprisedofdifferenttypesoffacilitiesandcapabilities.Theyinclude:

Knowledge-basedresources,suchasUKBiobank26,whichisanationalandinternationalhealthresourcethatprovidesresearcherswithaccesstoclinicalandbiomedicalinformationon500,000volunteerstoimprovetheprevention,diagnosisandtreatmentofserioushumandiseases

Distributed, major multi-user capabilities suchasELIXIR,thepan-Europeanresearchinfrastructureforbiologicalinformation,comprisingahubandnationalNodeswithtwenty-twomembersfromtwenty-onecountries.TheUKhoststheELIXIRhubattheWellcomeGenomeCampusandhasaUKnationalnodecomprisingfifteenUK-basedorganisations

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Networksofcutting-edgeprecisionequipment,suchasthoseestablishedthroughtheClinicalResearchCapabilitiesandTechnologyInitiative27,incloseproximitytoclinicalinvestigationandcarefacilitiesinordertoadvanceclinicalresearch

National centresaddressingresearchareasofnationalsignificance,forexamplesupportingfarmingandagriculture,orsupportingwellbeingthroughthedevelopmentoftheannualinfluenzavaccine.ExamplesincludetheWorldInfluenzaCentreattheFrancisCrickInstitute28andthenationalandinternationalreferencelaboratoriesforviraldiseasesatThePirbrightInstitute29

Food Nutrition And Health - 155

Biotechnology - 175

Environmental Science - 211

Neuroscience And Mental Health - 115

Drug Discovery - 135

Healthy Ageing - 128 Cohorts/population Studies - 120

Clinical Studies - 116

Cancer - 132

Computational Biology And Bioinformatics - 150

Forestry - 61

Ecology - 112

'omics - 175

Chemical Biology - 116

Molecular Biology - 189

Microbiology - 160

Biochemistry - 172

Biophysics - 107

Structural Biology - 112

Target Validation - 89

Crop Science And Agriculture - 141

Bio/biomedical Imaging - 136

Biological Techniques And Methods - 241

Bioenergy And Industrial Biotechnology - 99

Synthetic Biology/gene Editing/bioengineering - 98

Animal Health/veterinary Science - 83

Plant Science - 145

Evolutionary Biology - 103

Cell Biology - 132

Systems Biology/mathematical Biology - 126

Physiology - 93

Immunology - 103

Developmental Biology - 85

Stem Cells - 73

Regenerative Medicine - 73

Aquaculture - 57

Psychology - 64

Genetics - 161

SSAH72 E-INF

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Energy57

ENV120

PS&E116

244BH&F

Figure 9.1. Overlap(co-occurrence)ofresearchandinnovationinfrastructuresbetweenthebiologicalsciences,healthandfoodinfrastructuressectorandothersectors.Thesizesrelatetotheproportionofinfrastructuresthatoverlap(co-occurrence)basedonthenumberofresponsesthatselectedeachsector.Therearestronginterdependencieswiththecomputationalande-infrastructure,physicalsciencesandengineeringandenvironmentsectors.Acknowledgement:Sci2Team25.

Figure 9.2. Breadthandoverlapofsub-disciplinesinbiologicalsciences,healthandfoodsector.Thesizeofthenodesrelatestothenumberofinfrastructuresthatselectedeachsub-discipline.Acknowledgement:Sci2Team25

Figure9.2illustratesthebreadthandoverlapofBH&Fsub-disciplinesthataresupportedbyinfrastructuresacrosstheUK,fromcropscienceandagriculturethroughtotargetvalidationfordrugdiscovery.Thesub-disciplines(representedbycolouredcircles)arebasedonthecategoriesusedbytheResearchCouncils’grantssubmissionsystem.

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Case study: Cohort data infrastructures

SomeoftheUK’soldestinfrastructuresarelongstandingdatacollections,e.g.the1936LothianBirthCohort.TheUKhousesmanyunique,historicalpopulationdatasetswhichwillgrowinhistoricalsignificanceovertime.Toensurethesedatacanbereusedinfutureyears,theyneedtobecuratedtoremainaccessibleastechnologychanges.

Thelargevolumeofpopulationdatabeinggeneratedinmodernstudiesandtheincreasingneedtolinkandintegratecomplexdatatosupporttheirinterpretationresultedinanewinformaticsresearchinstitute,TheFarrInstitute,beingestablishedin2012andanewsuccessorinstitute,HealthDataResearchUK,beingincorporatedin2017.Theseinvestmentswillsupporttheinterrogationoftraditionalclinical,biological,populationandenvironmentaldataandalsodatafromemergingdataformsforpublicbenefit,e.g.wearabletechnology.

Case Study: Rothamsted Research

Rothamstedisthelongestrunningagriculturalresearchinstitutionintheworld.ItishometotheLong-TermExperiments–theoldestcontinuousagronomic(field)experimentsintheworld–whichstartedbetween1843and1856andarestillrunningtothisday.Thesehistoricfieldexperimentscontinuetoserveasaninvaluableinfrastructureandscientificdataresource,whichremainsrelevantduetocarefulmanagementandapplicationofnewmethods.TheyincludestheBroadbalkWinterWheatExperiment,whichhasbeeninvestigatingwaysofimprovingtheyieldofwinterwheatthroughinorganicfertilisersanddifferentorganicmanuressince1843,providingauniquedataset(containing,forexample,172yearsofwheatgrainandstrawyielddataandsixty-nineyearsofweedsurveydata)andresultinginthepublicationofnearly600papers.

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Case Study: The National Virology Centre

ThecentreislocatedatThePirbrightInstitute(formerlytheInstituteofAnimalHealth),whichhasbeeninexistenceforover100years.ItwasinitiallyestablishedasacattletestingstationfortuberculosisandnowhousestheinfrastructureforoneoftheUK’sleadingvirusdiagnosticsandsurveillancecentres.Attheforefrontofinternationalvirusresearch,thesitehasbeenrecentlyredevelopedtoincorporateastate-of-the-arthigh-containment(SpecifiedAnimalPathogenOrderGroup4)laboratory,hometotheBBSRCNationalVirologyCentrewhichusesaninnovativegasketsystem,negativepressureandextensivehighefficiencyparticulatearrestance(HEPA)airfilterstopreventairescapingthebuilding.Thefacilityenablesscientiststoresearchdangerouspathogensandcombatzoonoticdiseasesthatcanspreadfromanimalstohumans(e.g.flu),highlycontagiouslivestockviruses(e.g.bluetongueinsheep,Marek’sdiseaseinchickens)andfutureviralthreats(e.g.Africanswinefevervirus).

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TheinfrastructuresthatrespondedtothequestionnaireswerelargelyUKResearchandInnovationfunded/part-fundedprojectsbutalsoincludedanumberofclinicalresearchinfrastructures,fundedthroughothermeans,e.g.theDHSC.TheUKhasarichclinicalinfrastructure,e.g.anetworkofbiomedicalresearchcentres,bio-resourcesandclinicalresearchfacilities,whichismoreextensivethanthepresenteddataindicate.

ManyUKinfrastructuresarefundedthroughcompetitiveprocesses.Theyareawardedfundsbasedonresearchstrengthssotendtobelocatedclosetotheacademicuserbase.Thelinktouniversitieswashighlightedinthequestionnairewith88%ofinfrastructuresbeinghousedwithinanotherlegalentity(e.g.universityorbespokeresearchinstitute).Ofthese,71%wereconsideredalong-termfacilityorresourceandtheremaining17%werereportedasbeingdependentuponshort-termexternalfunding(Figure9.3).

InfrastructuresintheBH&Fsectorarelong-terminvestments(Figure9.4).Almost20%ofBH&F

infrastructureshavebeenoperationalforovertwenty-fiveyearswith10%havingexceededfortyyears.AlthoughFigure9.4suggestsalargeincreaseinnewinfrastructuresinrecentyears,thedatadonotillustratethecomplexpictureregardingthelifecycleofinfrastructures,suchasthelevelofturnoverofexistinginfrastructures,therepurposing/re-developmentoflongstandingfacilities,ortheriseofnewinfrastructurestosupportandmaximisepreviousinvestments.

Overthreequartersofinfrastructuresexpectthattheiroperationallifespanwillexceedfifteenyearsandthemajorityoftheseexpectthistobeovertwenty-fiveyears.Thedifficultyinsecuringlong-termoperationalfundingisborneoutbythedisparityinthedatabetweentheenvisagedlife-spanofaninfrastructureandthetimehorizonforwhichaninfrastructureisconfidenttoplanahead.Nearlytwothirdsofrespondentswereunabletoplanoverthreeyearsinadvanceandfewerthan10%couldconfidentlyplanbeyondasix-yearhorizon.Thiswillhaveimplicationsforbothstrategicplanningandtheoverallefficienciesthatcouldbeachievedwithgreatercertaintyoffunding.

17%

71%

9%

3%


Long-term facility/resourcewithin another entity



0%

10%

20%

30%

40%

50%

60%

Up to 5 years 5-15 years 15-25 years Over 25 years

Years since operations began Expected operational lifespan

Figure 9.4. Numberofinfrastructuresgroupedaccordingtothenumberofyearssinceoperationsbeganandtheirexpectedoperationallifespan.

17%

71%

9%

3%


Long-term facility/resourcewithin another entity



Figure 9.3.Legalnatureofinfrastructuresinthebiologicalsciences,healthandfoodsector.

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AlmostaquarterofinfrastructuressupportingtheBH&Fsectoraredistributed(comprisedofmulti-sitefacilities)orvirtual(e.g.accesseddigitally)(Figure9.5).Withthese,thehighestcostoftenisnotintheinitialconstructionbutinthelong-termrecurringcostsrequiredforrunning,maintainingandreplacing/updatingfacilities.

Thefuturespreadandnatureofinfrastructuresmayalterasscientificresearchshifts.Untilrelativelyrecently,researchhaslargelybeendeliveredthroughindividualresearchgroupseachwithaccesstotheirownlocalequipmentandfacilities.However,thereisanincreasingshifttowardsholisticapproachesmorereliantonlargedistributedteamswithcommonaccesstoinfrastructure,viaamulti-userregionalor

nationalplatform.ThischangeinapproachishighlightedbytheincreasingnumberofESFRIinfrastructuresthattheUKisamemberof.

Collaborationis‘businessasusual’,with92%ofinfrastructuresreportingthattheycollaboratewithotherorganisations.Ofthese,80%collaboratebothnationallyandinternationally.OverseasusersareattractedtoUKinfrastructuresforavarietyofreasons(Figure9.6),includingtheneedtocollaborate,theuniquenessofinfrastructureshousedhereandco-locationwithcomplementaryfacilities,e.g.accesstoclinicaloragri-techfacilities.ThemajorityofBH&Finfrastructures(61%)alsoprovideresourcesorrelatedservicestothewidercommunity,beyondtheinfrastructureitself.

TheEuropeanInfrastructureforMultiscalePlantPhenomicsandSimulation(EMPHASIS)isapan-Europeandistributedresearchinfrastructureonplantandcropphenotyping.Itisacollaborationinvolvingtwenty-fourcountriesandisaprojectoftheESFRIroadmap.EMPHASISwilladdressresearchquestionsaimedatimprovingcropresiliencethroughin-depthunderstandingofcropperformanceandphysiologyinreal-worldenvironments,byenablingaccesstoasuiteofpan-Europeanfacilitiesinrelevantgeographical/climaticzones.UKinfrastructurerelevantinaddressingsuchchallengesincludes:

TheInstituteforSustainableFood(UniversityofSheffield)whichoffersnext-generationclimatecontrol,analyticalandplantdiseasephenotypingfacilitiesacrossdisciplinestoenablediscoveriesanddeliverreal-worldsolutionstoachievefoodsecurity

TheHounsfieldFacility(UniversityofNottingham)whichisamultidisciplinaryresearchcentreemployingstate-of-the-artimagingtechniques,suchasX-Raycomputedtomographyandlaserablationtomography,tounderstandplantandsoilinteractionsandtheirresponsestoenvironmentalstresses

ThenationalphenotypingnetworkPhenomUKwhichwillenablecoordinationataUKlevel.Thiswillbuildonnewadvancesinfundamentalengineeringandphysicalsciences,bringingthenecessarydisciplinesintoclosercontactandpromotinganintegrated,holisticviewofplantandcropphenotypingacrosstheUK

Case study: EMPHASIS and UK plant and crop phenotyping

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68%

20%

4%8%

Single site

Distributed

Virtual

Mixed model Figure 9.5.Distributionofinfrastructuresaccordingtowhethertheyaresingle-sited,distributed,virtual,orhaveamixedmodelof morethanoneoftheseoptions.

0% 10% 20% 30% 40% 50% 60% 70%

Other

Similar capability has no capacity/long wait times

Part of a bi- or multilateral agreement

Availability of funding

Contractual

Location is not a consideration (e.g. for a digital service)

Higher quality than other options

Part of international collaboration

The 'package' (e.g. complementary facilities)

No similar capability elsewhere

Figure 9.6. Reasonsgivenforattractinginternationaluserstobiologicalsciences,healthandfoodinfrastructures.Optionswerenotmutuallyexclusiveandrespondentscouldselectasmanyaswereapplicable.

68%

20%

4%8%

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Distributed

Virtual

Mixed model

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9.2 Interdependency with e-infrastructure

‘Bigdata’wasoncethepurviewofastronomersandhigh-energyphysicists.However,theadventofnewhigh-resolutionimagingmodalities,theincreasinguseofautomated,high-throughputapproachesin‘omicsandtheadvancesinphenotypinghaveledtoincreasingcollections ofcomplex,multi-modalbiologicaldatathatrequireanagilee-infrastructureenvironmenttosupportthem.

E-infrastructureunderpinsthemajorityofBH&Finfrastructures,with73%havingasignificante-infrastructureand/ordatarequirementorcomponent.MostBH&Finfrastructures(82%)considerthate-infrastructureanddatawillincreaseinimportancefortheirinfrastructureoverthenextfivetotenyears.Thishighlightstheincreasingchallengefortheresearchcommunityinanalysing,integrating,managingandderivingnewknowledgefromthehugevolumeofdata.

TheBH&Fcommunityisstartingtoharnesstheopportunitiestoutilisedata-ledapproachessuchasartificialintelligence(AI)togaindeeperinsightsintofieldssuchasoncology,understandingtherulesoflife,e.g.throughlinkinggenotypetophenotype,investigating theeffectsofenvironmentonbothgenotype andphenotypeandimprovingthesustainabilityandresilienceofagriculture.Inaddition,the

desiretovirtuallylinkpopulation-leveldata (e.g.healthandroutineadministrativedata) withpatient-leveldatatoallowacomprehensiveviewofpublichealth(e.g.DataLinkageScotland30)willleadtoadditionaldataande-infrastructurerequirements.

Attheinternationalscale,theEuropeanBioinformaticsInstitute(EBI)31basednearCambridgeispartoftheEuropeanMolecularBiologyLaboratory(EMBL)32andisaworldleaderinbioinformaticsdataresourceprovisionandthecentreofglobaleffortstoanalyse,storeanddisseminatebiologicaldata.ThedataresourceshostedatEMBL-EBIarecriticallyimportantforlife-scienceacademicandcommercialresearch,receivingoverthirty-eightmillionwebrequestsperday.TheEBIalsohostsanumberofkeynationalandinternationaldatainfrastructuressuchasthehubofELIXIRandOpenTargets,asuccessfullarge-scaleindustrialcollaborationinpre-competitivedrugdiscovery.

9.3Engagementwiththe wider economy

ThetopeightsectorsoftheeconomybeyondresearchandeducationthatbenefitfromaccesseitherdirectlytoBH&FinfrastructuresorthroughthescientificoutputstheysupportareshowninFigure9.7.Someofthetopsectorssupportedarehealthservices,agriculture,thepharmaceuticalindustryandthefoodindustry.Therearealsostronglinkstopublicpolicy.

Figure 9.7.Topeighteconomicsectorstowhichbiologicalsciences,healthandfoodinfrastructurescontributetoorworkwith,excludingresearchandeducation.

Agriculture105 (46%)

Services: Health133 (58%)

Manufacturing: Pharmaceutical98 (43%)

Public Policy

74 (32%)

Manufacturing: Chemicals43 (19%)

Manufacturing: Food & Beverage59 (26%)

Forestry37 (16%)

Services: Computing & Communciations

37 (16%)

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MostresearchwithintheBH&Fsectoristowardsdiscoveryscience(64%).ThemajorityofinfrastructuresintheBH&Fsectorhavesomeengagementwithindustryas76%ofinfrastructuresreporteddoing‘some’,‘most’or‘all’oftheirworkwithUKbusinesses.Only4%ofinfrastructures’outputfocusesprimarilyoncommercialisation,though33%conducta‘balanced’portfolioofresearchandinnovation.

Engagementwiththecommercialsectorismoreevidentinsomeofthelarge,independentresearchpartnershipprojectsorthosesetupwithinnovationortranslationasakeygoal. Forexample,theMRC/AstraZenecaCentre forLeadDiscoveryallowsacademic researchersaccesstoindustryinfrastructure,e.g.highthroughputroboticdrug-screening

capabilitiestosupportdiscoveryanddevelopmentofsmallmoleculetherapeutics.Anothervehicleforsupportingthepull-throughofdiscoverysciencetoindustryisviaenginessuchastheCellandGeneTherapyCatapult,whichhelpstotranslateresearchexcellenceintocommerciallysuccessfulbusinessesfortheUK.AnadditionalapproachistakenbythefiveBBSRCResearchandInnovationCampuseswhereeachcampusiscentredonacriticalmassofworld-leadingbioscienceprovidingauniqueenvironmentwherefledglingbioscience-basedcompaniescanaccessspecialistfacilitiesandexchangeideaswithleadingresearchers,creatingalow-riskenvironmentforhigh-riskinnovation.Thecampusesfocusonareasrangingfromtheagri-techindustrythrough tomedicalbiotechnology.

Case study: Accelerating therapeutic discovery: Cell therapies

Translationisalong-termprocessrelyingonthepull-throughofdiscoveryscienceintonewproducts.AutolusLtd,abiopharmaceuticalcompanyfocusedonthedevelopmentandcommercialisationofnext-generationengineeredT-celltherapiesforhaematologicalandsolidtumours,becamethefirstcompanytoentertheCellandGeneTherapyCatapult’smanufacturingcentreinStevenage.AutolusisaUniversityCollegeLondonspin-outcompany,builtontenyearsofBBSRCandMRCfundingandtranslatedfurtherthroughtheNIHRBiomedicalResearchCentreatUniversityCollegeLondonHospital.

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Chapter 10: Physical sciences and engineering sector

Gerd Altmann from Pixabay

Case study: National Physical Laboratory (NPL) infrastructures

NPListheUK’snationalmeasurementinstitute.ItprovidesmeasurementcapabilitytoUKscientistsandbusinessesthrough380state-of-the-artlaboratories,withregionalcentreslocatedacrosstheUKprovidinglocalaccesstofacilitiesandexpertise.NPLdeliverssolutionstosomeoftheUK’sbiggestchallengesandopportunitiesinadvancedmanufacturing,health,energy,environmentanddigitaltechnologies.

AtomicTimedevelopedbyNPLinthe1950snowservesahugeindustryofdigitalandlocation-basedservicesfromGPSandmobilephonestobankingtransactionsandhigh-frequencytrading.InthefuturemoreaccurateandresilienttimefromNPLwillsupportautomatous-vehiclessafety,quantumtechnologycommercialisationandthedeliveryofnewenergysupplies.

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Thephysicalsciencesandengineeringresearchandinnovationspectrumspansallbranchesofphysics,chemistry,mathematics,materials,informationandcomputingtechnology,quantumtechnologies,healthcaretechnologies,engineeringandmanufacturing.

BecauseofthebreadthofresearchbeingcarriedoutacrossPS&E,thesupportinginfrastructuresarealsonaturallybroadintheirnature,includingspecialisedlarge-scaleequipment,facilities,institutionsandobservatories.Theseinfrastructuresincorporatecapabilitiesrangingfromlasersandacceleratorstomassspectrometry,NMRandimaging.Thisbroadrangeofcapabilityisessentialtodevelopingnewandmoresophisticatedtechnologiesthatcanrevolutioniseresearchandinnovationacrossallsectors.

Physicalsciencesandengineeringinfrastructureshaveenabledsomeofthemostimportantdiscoveriesandadvancesofthetwenty-firstcentury.In2012theHiggsbosonwasobservedalmostfiftyyearsafteritsexistencewasfirsttheorisedattheLHCatCERN.Usingtechnologiesdevelopedinthesector,cryo-electronmicroscopy(cryo-EM)hasbeenevolvedandtheUKnowhostsanationaluserfacilityforthestudyofbiologicalstructuresfromthemoleculartothecellularlevel.GraphenewasfirstisolatedbyresearchersattheUniversityofManchesterworkingonaninstrumentdevelopmentproject.Theuniquepropertiesofthematerialmeanitcouldhaveavastarrayofpracticalapplicationsincludingthecreationofnewmaterialsandthemanufactureofinnovativeelectronics.TheNobelPrizeforPhysicsin2010wasawardedtoProfessorsGeimandNovoselovfromManchesterfortheirground-breakingworkwhichisnowbeingtakenforwardattheNationalGrapheneInstitute.

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10.1 The current landscapeOveraquarter(27%)ofinfrastructuresthatrespondedtotheUKResearchandInnovationquestionnairenamedPS&Eastheirprimarydomain,whilealsosupportingsciencefromacrossallothersectors.Figure10.1highlightsthestrengthofoverlapbetweeninfrastructuresinthePS&Esector(centralcircle)andtheothersectors.TherearestronginterdependenciesacrosstheBH&F,environmentandenergysectors.

OnecommonapproachtoinfrastructureinthePS&Esectorisco-locationincampuses,whichbringtogetheranecosystemofinfrastructurestodelivercomplexcapabilities.TheHarwellandDaresburycampusesco-locatehigh-techcompaniesalongsidethenationalmulti-sectorfacilities,fosteringcollaborationandinnovation.

Theinterconnectivitybetweeninfrastructuresisparticularlyimportant,forexamplebetweenlab-based,distributedfacilitiesandlarge-scalecampus-basedfacilities.Asthescaleofneedstretchesbeyondtheabilityofindividualorganisationstofinance,procureandprovide

thenecessarysupportinfrastructures,therehasbeenamovetowardsadistributednetworkmodelforfacilitiessuchastheEngineeringandPhysicalSciencesResearchCouncil(EPSRC)NationalResearchFacilities.Thesesupportstrategicresourcesofnationalimportancetoprovideleading-edgecapabilitiesandtechniquedevelopmentatanationallevel.

However,themajorityofPS&Einfrastructuresaresinglesite,focusedcapabilities,typicallyhousedwithinanotherlegalentitysuchasauniversity.Asignificantnumberofcapabilitiesarespreadacrosstheglobe(e.g.theJapanProtonAcceleratorResearchComplexandtheLarge-apertureSynopticSurveyTelescope,currentlyunderconstructioninChile)andsomeinfrastructuresareevenbasedinspace(e.g.theInternationalSpaceStation).Aswellasthesesingleinfrastructures,therearealsoco-locatedfacilitieswithmultipleinfrastructuressuchassuitesoftelescopes(e.g.ESO)ordetectors (e.g.theJeffersonLab)andmultiplecapabilities,suchastheNationalPhysicalLaboratoryinfrastructures.

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212PS&EThePS&Esectoriscentrallyplacedandtheperipheralnodesrepresenttheothersectors.ThesizesrelatetotheproportionofinfrastructuresthatoverlapwiththePS&Esector(co-occurrence)basedonthenumberofresponsesthatselectedeachsector.

Figure 10.1.Overlapbetweeninfrastructureswithaprimaryaffinitytothephysicalsciencesandengineeringsectorandtheothersectors.Acknowledgement:Sci2Team25.

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Case study: Space-based telescopes

TheJamesWebbSpaceTelescope(JWST)willbethebiggestspacetelescopeeverbuilt.DesignedandbuiltbyNASAinpartnershipwiththeCanadianandEuropeanSpaceAgencies,itisdueforlaunchin2021.TheJWSTwillorbitindeepspace,1.5millionkmfromEarth,onamissionofatleastfiveyears.

AsthesuccessortotheHubbleSpaceTelescope,theJWSTisexpectedtoproduceevenmoreastoundingimagesoftheUniverse.ThetelescopewillbeabletoexplorethedistantUniverseandtheevolutionofplanets,starsandgalaxiesasneverbefore.Itwilllookbackintimeto400millionyearsaftertheBigBang,allowingustoseethefirstobjectsthatformedastheUniversecooled.TheUKledtheEuropeanconsortiumtobuildtheMidInfraRedInstrument(MIRI)fortheJWSTandwasalsoresponsiblefortheoverallconstructionoftheinstrumentandthequalitycontroltoensurethatMIRIwilloperateasintendedandcopewiththeharshconditionsofspace.

AkeyattributeofinfrastructurewithinPS&Eisitslongevity.Thereareahighnumberofinfrastructureswithanexpectedlifespanofovertwenty-fiveyears,reflectingthesize,complexityandphysicalnatureoftheinfrastructurestypicalofthissector.Anumberofthelarger,longer-runninginfrastructuresarealsomultidisciplinaryinnature,asshowcasedinChapter2.2.Althoughthesectorcontainsalargeproportionoftheselong-runninginfrastructures,thereisalsocontinualgrowthandinvestmentinnewresearchcapabilities.Since2015anumberofnewinstituteshostingsignificantinfrastructurehavebeensupported.TheseincludeTheAlanTuring

Instituteindatascience,theFaradayInstitutioninbatteryscienceandtechnology,theHenryRoyceInstituteinadvancedmaterials,theUKCollaboratoriumforResearchonInfrastructureandCities(UKCRIC)andmostrecently,theRosalindFranklinInstitute,focusedontransforminglifesciencethroughinterdisciplinaryresearchandtechnologydevelopment.

GiventhelonglifetimesofmanyPS&Einfrastructures,thereisaneedtofactor-incontinuoustechnicaladvancementsthroughouttheirlifecycles.Theseadvancementsensuretheinfrastructuresareabletoremainfitforpurpose,

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Figure 10.2. Classificationandsub-sectorgroupingofthephysicalsciencesandengineeringresearchandinnovationinfrastructures.

suchasbeingabletohandleincreasinglylargedatasets,dealingwithchallenging/extremeenvironmentsandcopingwiththeneedforgreatertechnicalandanalyticalexpertisetomaximisethescientificoutputs.

Physicalsciencesandengineeringinfrastructures,suchastheLHCatCERN,havefacedsomeofthemostextreme‘bigdata’challenges,andwithinfrastructuresgeneratingevergreatervolumesofdata,therelianceone-infrastructurefacilitiesandexpertiseisexpectedtoincreaseovertime.SeventypercentofPS&Einfrastructuresenvisagee-infrastructureanddatabecomingmorerelevanttotheirinfrastructuresinthenextfivetotenyears.

10.2CharacterisingthesectorPhysicalsciencesandengineeringinfrastructurescanbecharacterisedaseithercapability-anddiscovery-driven,application-drivenorchallenge-driveninfrastructurestodescribethescienceandinnovationtheytendtosupport(Figure10.2).Inmanycasesthedifferentinfrastructuresprovidecomplementaryexpertisetoeachother.Toanswercomplex,interdisciplinaryproblems,acombinationofapproachesmakinguseofinfrastructuresacrossthedifferentcategoriesisrequired,hencetheimportanceofthisinterconnectivity.

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Application driven infrastructure:Theseinfrastructureshaveanidentifiablerelevancetoindustrialsectorsorend-usergroupswithintheeconomysuchasaerospace,automotiveandspace.Thecomplexityoftheuserproblemswilloftenrequiretheseinfrastructurestobeusedinconcertwith otherinfrastructures.

TheNationalEpitaxyFacilitysupportsworld-classsemiconductorresearchintheUK,providingarangeofsemiconductormaterialsanddevicestoacademicsandindustrialcustomers.

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Challengedriveninfrastructure:Theseinfrastructurestendtobepartofwiderinitiativestargetedtowardsaddressingmajorscientific,technical,innovation,societalorpolicychallengesforwhichadditionalgovernmentfundinghasbeencommitted. Theyoftenbuildonoutstanding,existingcapabilitywhichhasbeenbuiltupovermanyyearsthroughcapability-driveninvestments.

Forexample,theNationalRobotariumwillexpandonexistingfacilitiestocreateaunique,world-leadingcentreforthepracticalapplicationofroboticsandautonomoussystemsinareasasdiverseashealthcare,manufacturingandhazardousenvironments.

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Capability and Discovery driven infrastructure: Infrastructureofthiskindprovidestheessentialcapabilitythatallowsustodesign,model,synthesise,characteriseandtestmaterialsatdifferentlengthscales(fromatomicscalethroughtocomponents)andtoenablediscovery.Itincludelarge-scale,campus-basedfacilitiesaswellasdistributedandofteninternationally-basedstate-of-the-artinfrastructuresandmajoruniversity-basedclustersofcapability.

TheLHCatCERN,theworld’slargestandmostpowerfulparticleaccelerator,ishelpingscientistsunderstandthefundamentallawsofnatureand,forexample,enabledthediscoveryoftheHiggsbosonparticlethatprovedhowparticlesgainmass.

CERN

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Case study: National Wind Tunnel Facility

Aninvestmentof£14.5Min2015developedandupgradedasuiteofseventeennationalwindtunnelfacilities(NWTF).TheinvestmentisaimedatkeepingtheUKattheforefrontofaerodynamicandfluidmechanicsresearch.InfrastructureisavailabletoallUK-basedresearchersandaimstocreatenodesofexcellenceattractingyoungresearchers.TheNWTFalsoaimstoestablishaclosertiewithindustry,creatingapull-throughenvironmentandanintendedspill-overofthecollaborationandbenefitstoothersectors.

Bringingtheseventeenfacilitiestogethertoprovideaservicethatisgreaterthanthesumofitsindividualtunnelshasallowedamodeltodevelopthatprovidesstrategicoversightandmanagementoffacilitiesinasharedmanner.Italsoensuresacollaborative,alignedapproach.

10.3 The importance of international collaboration

Researchinthissectorincreasinglyreliesonsophisticatedexperimentsatarangeofbespokenationalandinternationalfacilities,oftenattheleadingedgeofwhatistechnicallypossible.Duetothescaleandcostsofsuchfacilitiesmanyinfrastructurescanonlyberealisedthroughinternationalcollaborationsandlong-termstrategicplanning.Thisisverytypicalofthecapability-driveninfrastructuresthatprovideinsightsintothefundamentalbuildingblocksofmatterortheoriginanddevelopmentoftheUniverse,suchastheFacilityforAntiProtonandIonResearchinEurope(FAIR)currentlybeingbuiltinGermany.Forthisreason,thePS&EsectorhasthelargestproportionofinfrastructureslocatedoutsidetheUK.

10.4 ImpactsPhysicalsciencesandengineeringinfrastructuressupportadiversityofeconomicsectorsbeyondresearchandeducation(Figure10.3).Withoneexception,eachofthefortyeconomicsectorchoiceswasselectedbyatleastonePS&Einfrastructure.Physicalsciencesandengineeringinfrastructuresareparticularlyimportanttothemanufacturingandtransportationeconomicsectors.CloselinkswithindustryacrossthePS&Esectorarereflectedbythefactthat86%ofPS&Einfrastructuresperformatleastsomeworkthatisdirectlyinformedbybusinesses.

TheimpactsofthescienceandutilisationoftechnologiesdevelopedwithinthePS&Esectorareextreme,influencingoureverydaylives.TheCompactLinacatDaresburyLaboratoryhasbeendevelopedtoinvestigatethepotentialforsmall,low-energylinearacceleratorstobeutilisedinareassuchassecurityandwastewatertreatment.ResearchbyBristolRoboticsLaboratoryinthefieldofground-breakingroboticsystemsenablessurgeons toputjointfracturesbacktogetherusing aminimallyinvasiveapproach.

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Manufacturing: Electronics94 (55%)

Manufacturing: Instrumentation97 (57%)

Utilities: Energy80 (47%)

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Manufacturing: Pharmaceutical67 (39%)

Transportation: Automotive75 (44%)

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66 (39%)Manufacturing: Transportation

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InfrastructurescanhaveimpactsonourfundamentalunderstandingoftheUniversearoundus,helpingustoanswerquestionsthatweareonlyjustbeginningtocontemplate.Forexample,UKscientistsandengineersplayedkeyrolesintheconstructionandoperationoftheLaserInterferometerGravitational-WaveObservatory(LIGO),whichrunstwodetectorsintheUSA,andtheVirgogravitational-wavedetectorinItaly.

Afterthefirstdetectionofgravitationalwavesin2016,LIGOandVirgorecentlydetectedgravitationalwavesfromwhatappearstobeacollisionbetweentwoneutronstarsabout500millionlightyearsfromEarth.Neutronstarsarethedenseremnantsofmassiveexplodedstars.Justonedaylater,thenetworkregisteredanothereventabout1.2billionlight-yearsaway;initialanalysissuggestsitmighthavebeenthecollisionofaneutronstarandblackhole.

Figure 10.3.Topeighteconomicsectorstowhichphysicalsciencesandengineeringinfrastructurescontributetoorworkwith.

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Chapter 11: Social sciences, arts & humanities sector

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Infrastructuresinthesocialsciences,artsandhumanitiessectorareusedbyresearchersfromabroadrangeofdisciplines.Socialsciences,artsandhumanitiesinfrastructuresarealsousedextensivelybypolicy-makersacrossgovernment,bythethirdsectorandbythewiderpublic.TheyaregloballyvisibleasexamplesoftheUK’sleadingroleinresearchandinnovationandahighproportionengagewithbusiness.

Socialsciences,artsandhumanitiesinfrastructuresincludetoolsandtechniquessuchasclustersofexpertcapabilityandprovisionofhardwareorfacilities.Manyinfrastructurescollectorfacilitateaccesstoresearchobjects,includingphysicalresourcessuchashistoricartefactsandvirtualresourcessuchassocialsciencedata.OtherdistinguishingfeaturesoftheSSAHinfrastructuresincludelargeuserbases,diversifiedandshort-termfundingmodelsanddispersalacrossmultiplelocations.Socialsciences,artsandhumanitiesinfrastructuresarecharacterisedbydisciplineagnosticism.Amongrespondents,95%ofinfrastructuresinvolvemultiplesubdisciplinesofSSAHand69%reportrelevancetosectorsbeyondSSAH.

Of751respondentstothequestionnaire,110infrastructuresidentifiedSSAHastheirprimarysector.Ofthese,107arebasedintheUK.Respondentsincludedamixtureoftargetedandself-identifiedinfrastructures.SomedisciplineswithinSSAHarelessfamiliarwithusingtheterm‘infrastructure’todescribewhattheyofferandmayhavebeenslowertoengagecomparedtoothersectors.

11.1 Form and function of infrastructures

Inthissector,95%ofinfrastructureshaveapresenceataphysicallocation,49%ofinfrastructuresaresingle-sitedand16%aredispersed(Figure11.1).Overall,73%ofinfrastructuresrespondingoffersomelevelofvirtualaccess,butonly5%identifyasentirely‘virtual’ordigitalinnature.Insomecases,infrastructuresarecloselylinked.Forinstance,sensitivedataresourcesbenefitfromotherinfrastructuresforcollection,storage,analysisandfacilitatingresearcheraccess,whilebeinginfrastructuresthemselves.

Broadly,SSAHinfrastructuresoperateacrossaspectrum,rangingfromprimarilyservicedeliverythatisdependentonexperthumanresource,tohardwareandfacilitiesprovision.Someinfrastructureshaveamixedmodel.TheUKDS,forinstance,hassecurefacilitiesfordatastorageanduserfacilitiesandoffersadviceservices.

FormanySSAHinfrastructuresthepresenceofspecialistsembeddedwithintheinfrastructureforactivitiessuchasprocessingresearchdataorcuratinghistoricartefacts,orprovidingtrainingoradvice,isakeyandessentialpartoftheinfrastructure.Maintaininganddevelopingsufficientexpertcapabilityisanongoingchallenge.Theseinfrastructures’purposecanbetobuildcapabilityamongstresearchers,oramongstresearchdataoroutputusersfromgovernmentorthethirdsector.Someinfrastructuresexisttoenhancetheuseofresourcesororganisationsthatareinfrastructuresthemselves.TheCohort&LongitudinalStudiesEnhancementResources(CLOSER)andtheNationalMuseumsCollectionCentreareexamplesofthis.

49% 5% 29% 16%

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Figure 11.1. Typeofsocialsciences,artsandhumanitiesinfrastructures.

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Case study: CLOSER’s informs recommendations on early years intervention

CLOSERisacollaborationofUKsocialandbiomedicallongitudinalstudies,theBritishLibraryandtheUKDS,fundedbytheEconomicandSocialResearchCouncil(ESRC)andtheMRC.TherearecurrentlyeightstudiesintheCLOSERpartnership,comprisingfournationalandthreeregionalbirthcohortstudiesandUnderstandingSociety(theUKHouseholdLongitudinalStudy).

In2018,CLOSERsubmittedevidencetotheHouseofCommonsScienceandTechnologyCommittee:Evidence-basedEarlyYearsintervention,onthecontributionoftheUK’slongitudinalstudiesasleadingsourcesofevidenceonhowearlycircumstancesandexperiencesaffectpeople’slivesfromchildhoodtoadulthood33.Forexample,researchusingtheMillenniumCohortStudy,1958NationalChildDevelopmentStudy,1970BritishCohortStudyandUnderstandingSociety,hasshownhowfactorssuchasmother’shealthduringpregnancy,child’sbirthweight,parents’educationandemploymentandfamilyhousingandsocio-economiccircumstancescanhavealastingeffectonchildren’scognitive,socialandbehaviouraldevelopment.Inparticular,beingbornintopovertyordisadvantagecanhavelastingeffectsonhealth,education,employmentandageing.CLOSERalsohighlightedthepotentialoflinkingadministrativedataheldbythegovernmenttothislongitudinalsurveydatatogeneratenewinsights.

Thisevidencewascitedinthecommittee’sreport34andsupporteditsrecommendationtogovernmentthatacademicresearchersbeenabledtoaccessgovernmentadministrativedata(whileensuringappropriateprivacyandsafeguardingmechanismsareinplace).Thegovernmenthascommittedtoprovidingsecureaccesstode-identifieddataforaccreditedresearchers35andiscurrentlyworkingonthedevelopmentofAdministrativeDataResearchUK(ADRUK).Thisissupportedbya£44millioninvestmentfromESRCandwillbesetupincollaborationwiththeOfficeforNationalStatistics.ADRUKwillprovideaccesstodatafromgovernmentdepartments,localauthoritiesandhealthauthoritiestoanswervitalresearchquestionsonearlyinterventionandchildhoodadversity.

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ManyinfrastructuresintheSSAHdomaininvolvethesubstantiveprovisionofhardwareorfacilities.Thiscanincludeprovidingsecureplacessuchas‘safepods’inuniversitylibrariesfortheanalysisofpersonaldata,ortoolsforuser-leddigitisationofhistoricarchives.Heritagescience(theuseofsciencetounderstand,manageandcommunicatethehumanstoryexpressedthroughlandscape,buildingsandartefacts)demandsincreasinglyspecialistexpertise,instrumentationandlaboratoryfacilitiesaswellasinvestmentintheintegrationofcapability.Formuseums,researchcanenabletheenhancementofcollectionsandspaces,forinstancebydevelopingnewcurationorvisualisationtechnologyorimmersivevisitorexperiences.Insomecases,providingresearcheraccessentailstrade-offswithotherdemands,forinstanceinmuseumsettingswhereobjectsandspacesareaccessibleto abroader,non-researcheraudience.

FundingmodelsforSSAHinfrastructuresarediverse.Theyincludeco-fundingagreementswithmajorcharities,internationalpartnershipagreementsandquality-related(QR)blockfundingawardedtohostuniversities.Governmentdepartmentsaresignificantfunders,particularlytheDCMS.Thirty-eightpercentofSSAHinfrastructuresattractnon-governmentalfunding.Artsinfrastructuresoftenhavehighlydiversifiedrevenuestreams,generatingincomethroughcommercialandphilanthropicactivity.Thisimprovesthecapabilityofthesectortoarticulatethepurposeandvalueofinfrastructuretoarangeofaudiences.Muchofthisfundingis,however,short-term,with19%ofrespondinginfrastructuresfundedthrough‘softmoney’withnocommitmenttolong-termsustainability.Otherbusinessmodels,suchaschargingfordataaccess,mayconflictwiththeprincipleoffreeandopenaccess.

TheSSAHsectorischaracterisedbyitsinfrastructures’accumulationofvalueovertime.Forinstance,museumcollectionsfacilitatecomparativeanalysisbybuildingincreasinglybroadandwell-documentedcollections.Longitudinalstudiesandrepeatcross-sectionalstudies(forinstanceofelections)alsoenableincreasinglycomplexinsightsasmoredatais

added.Socialsciences,artsandhumanitiesinfrastructuresarecharacterisedbytheirlongevity(seealsoChapter3.3).Theyaresomeoftheoldestandlongest-runninginfrastructuresintheUKwith34%originatingbefore1978and79%expectingtheirinfrastructure’slifespantoexceedtwenty-fiveyears.Thisholdsforthemanyservice-orientatedinfrastructuresaswellasphysicalresources(e.g.collections)whoseprimaryfunctionsaredeliveredthroughexpertcapabilityratherthanphysicalhardware.Longevityalsobringschallengessuchastheneedtostore,maintainandpreserveexpandingcollectionsofresearchobjectsoverthelongterm.

11.2 Research objects (physical and virtual resources)

IntheSSAHsector,90%ofinfrastructurescreate,collect,curateorprocessresearchobjectsasasignificantfunction.Theseobjectsarediverse,rangingfromuniquephysicalresourcessuchasartefactstovirtualoneslikestructureddatasetsforquantitativeanalysis.Researchobjects’provenancealsocoversabroadspectrum.Whilesomederivefrominstrumentation,particularlyintheheritagesciencefield,adistinguishingfeatureisthecreationofobjectsthroughothermethods.Thiscanincludesocialsurveyscollectedthroughfieldwork,consumerdataobtainedthroughpartnershipwithbusiness,orobjectsdepositedinmuseums.Indeed,manySSAHresearchobjectswerecreatedforpurposesotherthanresearch.Fromarchaeologicalfindstolargeadministrativedatasets,theirhandlingcreatesuniquechallengesandrequirementsforembeddedexpertise.Increasingly,datalinkageisenablinginfrastructuredatatobeusedinnewways,maximisingvalueanddrawingnewinsightsby,e.g.connectingdatacollectedspecificallyforresearchwithdatasetscreatedbygovernment.

ThereissignificantcapabilityacrosstheSSAHinfrastructurelandscapeinthecapture,processingandanalysisofcomplexdataaboutpeople.Complexitycanariseforanumberofreasons.Thecollectionmethod,forinstancesocialsciencesurveys,mayrequirecarefulconsiderationofrepresentativeness.Datamaybepersonalorsensitive.

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Inthecaseofnon-researchdata,suchasmedievalmanuscriptsorrecentadministrativedatasets,expertcurationmaybeneededbeforeobjectsareusableforresearch.Processingandprovidingaccesstosuchdatafrequentlyinvolvesworkingwithinlegal,ethicalandpublicacceptabilityframeworks.

Theongoingdigitisationofphysicalcollectionsgeneratesfurthercomplexdata,suchashigh-resolution3DmodelsofobjectsorXML-encodedtexts.Overall,enablingaccesstocomplexdata,maximisingvaluethroughcurationandlinkageandensuringsecureandethicalusearespecialismsoftheSSAHlandscape.Digitisationofresearchobjectsoffersopportunitiesforincreasedaccessandinternationalcooperationwhilepotentiallyloweringaccesscostsforusersandproviders.

Most(86%)SSAHinfrastructuresalsoserveotherdisciplines.Thisrequiresdepositprotocols,processingstandardsandaccessmethods,whicharediscipline-anduser-agnostic.ItalsofacilitatesthedevelopmentandapplicationofteachingmethodsandtoolsthathavevaluebeyondtheSSAHsector.Forexample,traineesurgeonshaveusedtextilecollectionstodevelopfinemotorcontrol,whileremote-imagingtechnologydevelopedforconservationpurposeshasbeenusedbystructuralengineerstoassessbuildingsafety.

Digitaltechnologyhaschangedthewaywecollect,mapandrepresentphysicalandvirtualresourcesandthewaywecanconnectwithresearchersandotheraudiencesonaglobalscale.Dataficationoftext,imageandsoundcoupledwithapproachestoallowpatternrecognition,statisticalanalysisandotherformsofsoftware-basedinterrogationhasopenedupthepossibilitiesfornewformsofdigitalresearchwithapproachessuchasuseofAI,conceptandentityrecognitionandvirtualisation.

Physicalartefactsbasedinuniversities,galleries,libraries,archivesandmuseums(GLAMs)andotherheritageorganisationsservethousandsofusersandtensofmillionsofresearchobjectrequestsperyear(Figure11.2).Manyofthesecollectionsareunique,irreplaceableandincreasinglyfragile,demandinghighlevelsofskillforaccess,conservation,interpretationandspecialistfacilitiesforstorageandanalysis.Continuousgrowthofpublicresearchobjectcollectionscanstemfromlegaldepositrequirements,legislativebarrierstoobjectdisposalandincreasedresearchobjectproduction.Thiscreatessignificantchallenges intermsofsitingsuchasincreasingstoragecosts,makingitdifficulttoreneworrelocate aninfrastructure.

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11.3 Impacts and outputsSocialsciences,artsandhumanitiesinfrastructurescontributeextensivelytosocioeconomicimpact,fromthedevelopmentofpublicpolicytodirectlyworkingwithbusinesses.Overhalf(57%)ofinfrastructuresworkwithbusiness(Figure11.3).Examplesofvaluetobusinessincludetheprovisionofattitudesoreconomicdataandcreationof,oradviceon,ethicalorlegalframeworkssuchascopyrightlawforbusinessactivity.Infrastructuresthatdevelopresearchcapacityinquantitativesocialscienceorheritagescienceinparticularalsogeneratesignificantvalueforthelabourmarket.Indeed,privatesectordemandforsuchcapabilitycreatessignificantchallengesforinfrastructuresthatdependonhumanexpertisefordelivery.

Socialsciences,artsandhumanitiesinfrastructuresenablegovernmentandbusinesstounderstandeconomicdriversandoutlooks.Longitudinaldataresourceshaverevealedthelabourmarketimpactsofvocationaleducation,forinstance,whileothersocial

scienceinfrastructureshaveworkedwithmajorretailerstounderstandcustomerorigins.Keyareasofengagementwitheconomicsectorsoutsideresearchandeducationincludethecreativeindustriesandrecreation(72%ofSSAHinfrastructures)andpublicpolicybroadly (63%ofSSAHinfrastructures)(Figure11.4).

Includedinthe72%ofinfrastructuresworkingwithcreativeindustriesandrecreationareworld-renownedGLAMsandheritageorganisationsthatareamongsttheUK’smainvisitorattractions,bothforlocalpopulationsandforvisitorsfromabroad,playingahighlysignificantroleinthemulti-billion-poundheritagetouristeconomy.AbouthalfofallvisitorstotheUKcitecultureastheirreasontovisit,withArtsandHumanitiesResearchCouncil(AHRC)IndependentResearchOrganisations(IROs)accountingforeightoftheUK’stenmostpopularattractions36 .ItisestimatedthatthenationalGrossValueAdded(GVA)oftheheritageeconomyis£29billionequatingto2%ofthenationalGVA,withheritagetourismexpenditurecontributing£16.9billion.

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Figure 11.3. Extenttowhichsocialsciences,artsandhumanitiesinfrastructuresdirectlyworkwithbusinesses.

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Case study: Using data analysis to support the National Online Hate Crime Hub

HateLab,partoftheESRC-fundedSocialDataScienceLab,makesuseofsocialmediadatatoinvestigatehatespeechandcrime.ResearchersatthelabhavedevelopedanOnlineHateSpeechDashboard37,incollaborationwiththeNationalOnlineHateCrimeHubandinconsultationwithallfourpoliceforcesinWales,GreaterManchesterPolice,theWelshGovernment,thegovernment’sBehaviouralInsightsTeamandseveralhatecrimecharities.

Thedashboardtrackstrendsofonlinehatespeechinrealtime,bygeographicalregion.Thisassistsanalyststoidentifyareasthatrequireoperationalandpolicyattentionandallowspoliceandsupportorganisationsbothtorespondmorequicklytospikesinhateandtopre-emptthespreadofhatespeechandcrimefollowing‘triggerevents’.Cruciallyitspeedsupaccesstothisinformationinthe‘goldenhour’aftersuchanevent.TheDirectoroftheNationalOnlineHateCrimeHubstatedthatefficienciescreatedbythedashboardhaveledtosavingsof£500,000.

Almostthreequartersofinfrastructures(72%)reportedsubstantivepolicyorpublicservicedeliveryimpact.Longitudinaldatainfrastructuresinthesocialsciencesenableinfluencesonhealthandeconomicoutcomestobeunderstoodacrossthelifecourse.Linkageofdatasetshasenabledincreasinglypowerfulanalysesinthisfield,generatingconsiderableadditionalvaluefrombothgovernmentdataandpubliclyfundeddataresources.Otherinfrastructures,suchastheWhatWorkscentres,evaluatepolicyeffectivenessorfacilitateaccesstopolicy-relevantresearch.

Policyrelevancecanberelativelyspecific(forinstance,thetax-benefitmicrosimulationmodelEUROMOD)orapplicabletoarangeofgovernmentresearchinterestareasatnationalandlocallevel.Administrativedatainfrastructuresoffernewopportunitiestoanswerquestionsofpublicimportanceinatimelymanner.

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Figure 11.4. Topeconomicsectors(inadditiontoresearchandeducation)whichinfrastructuresinthesocialsciences,artsandhumanitiessectorcontributetoorworkwith.

11.4Socialsciences,artsandhumanities infrastructure users

Apartfromdirectaccess,71%ofSSAHinfrastructuresprovideservicesandresourcestoawidecommunityofusers.Activitiescanincludeadvisingontheavailabilityandappropriateuseofresearchobjectsorprovidingtraining.Otherinfrastructuresdevelopmethodologyorpolicyonresearcherethics,curationofartefactsorobjectandmaterialsanalysis.Socialsciences,artsandhumanitiesinfrastructuresarecharacterisedbyopenaccessandhavethehighestrateofunrestrictedaccessacrosssectors(60%ofinfrastructures).Just6%requireaccesstobemediatedviaaninternaluser.

HeritageorganisationsandGLAMinfrastructuresinthehumanitiesservehundredsofthousandsofresearchusersfromoutsidepublicresearchorganisationseachyear.Theneedtofacilitatepublicaccessonaveryextensivescalegeneratesitsownchallengesintermsofaccessibilityanddiscoverabilityofcollectionsandtheirmaintenanceandpreservation.

Socialsciences,artsandhumanitiesinfrastructuresareinherentlyinternationaland96%haveusersfromoutsidetheUK.Almosthalfofrespondentssaidthatthecapabilitytheydeliverisgloballyunique,with81%notingthattheyattractinternationalusersduetolackofsimilarcapabilityelsewhere.Thesector’sinfrastructuresarehighlycollaborative(85%)nationallyandinternationally,attractinginvestmenttotheUK.Sixinfrastructuressurveyed,forinstance,attractmorethan20% oftheirincomefromEUfundingsources.


Services: Creative industries, recreation

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Case study: The Engine Shed

HistoricEnvironmentScotland(HES)isanIROenablingresearchthatprovidesanunparalleledviewofhowhumanactivityandinterventionhasshapedScotland.Itsresearchinfrastructuresupportsworld-classresearchinarangeoffields,includingsurveyingandrecording,heritagescienceandphysicalanddigitalarchiving.

TheEngineShedisScotland’sdedicatedbuildingconservationcentre,basedinStirling.PartofHES,itservesasacentralhubforbuildingandconservationprofessionalsandthegeneralpublic.TheEngineShedwasestablishedonthepremisethatScotland’sbuiltheritageholdscountlessstories–aboutthepeoplewhobuiltit,livedinitandusedit–andthatknowledgeofthepastprovidespointerstothefuture.Itsin-houseexpertsprovideadvicetotheheritagesectorandthepublictoensurebestpracticeandhelpraisestandardsinconservationoftraditionalbuildings.AspartoftheEngineShed’sinnovativetrainingforpractice-basedresearchinconservation,stonemasonryandtraditionalbuildingmaterialsandmethods,augmentedrealityand3Dprintingisusedtoenableaccuratereconstructions.Thisresearchalsodrivesaprogrammeofskills-basedpublicengagementwithlocalcollegesandschoolsaspartofawiderefforttoensurethat‘childrenofthedigitalage’remainconnectedtoandconfidentworkingwithphysicalmaterials.

TheEngineShedhousestheHESDigitalDocumentationTeamthatusescutting-edgedigitaltechnologiestodocumentheritagein3Dtoinformtheresearchthatunderpinssustainableconservation,heritagemanagement,learningandinterpretationefforts.Theteamgeneratestheresearchdatathatareusedforinteractivetoursandvirtualvisits,creatinginnovativeimmersivevisitorexperiences.HESispartoftheemergingUKResearchInfrastructureforHeritageSciencethatwilldriveaccesstotheseblendedfacilities,enhancingscientificresearchandcross-disciplinaryandinternationalcollaborations.

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Chapter 12: Environment sector

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Environmentalinfrastructureiscriticaltoreach,observe,model,simulateandpredictourcomplexenvironment,aswellastounderstandhowhumansimpactandareaffectedbyit,includinghealthandwellbeing.Environmentalresearchersstudytheentireplanet,fromthedeepoceansandthecentreoftheEarthtotheedgeoftheatmosphereandthehostileenvironmentsofthepolarregions.Thesectorhasastrongtrackrecordofdiscoveriesthatbringaboutaction,fromidentifyingtheholeintheozonelayertotheobservationsandmodellingrevealingtherisksofclimatechange.Environmentalscienceisessentialtoensuretheenvironment,peopleandbusinesssucceedtogetherinmeeting21stcenturychallenges.

Theglobalpaceofdemographicchangeisdrivingincreasinglysevereandfrequentenvironmentalimpactsfromgrowingdemandsandpressuresonenvironmentalresources.Environmentalinfrastructureiscriticaltoensurewater,foodandenergysecuritybymanagingtheEarth’sresources,boostingresiliencetonaturalhazards,enablingmitigationofandadaptationtoclimatechange,andmuchmorebesides.Thesechallengesarecoupledwithopportunities,duetotheincreasingavailabilityofenvironmentaldata,advancementofdigitalcapabilities,fast-paceddevelopmentinsensing,automationandAIandimprovedforecastingskillfromhourstodecades.

Risingtothecutting-edgesciencechallengesofourtimeanddeliveringenvironmental,economicandsocialsolutionstoreal-worldproblemsdemandsworld-leadinginfrastructure.Wealsoneedtobecognisantofthespecialistneedsoftheenvironmentsectorforinfrastructure.Acharacteristicoftheenvironmentsectoristhebreadthofscalesfromnanotoplanetary,fromsecondstomillionsofyearsandtheharshandhazardousenvironmentsoftenencountered.Totacklecomplexproblemsanddrivescientificprogress,wemustfacilitatewhole-systemapproachesthatensuretheUKenvironmentsectorleadstheworldinresearchandinnovationspanningscientificdisciplinesandborders.

12.1 Characteristics of the landscapeNinety-fouroftheinfrastructureswhorespondedtothequestionnaireidentifiedtheirprimarysectorasenvironment.Betweenhalfandthreequartersoftheremaining657infrastructuresintheotherfivesectorsalsoidentifiedenvironmentasasectortheirinfrastructurecovered(Figure12.1).Thisdemonstratesthebreadthandscopeoftheenvironmentsectorandhighlightsthecross-cuttingnatureofitsinfrastructures.Forexample,74%ofcomputationalande-infrastructuresalsoidentifiedtheenvironmentsectorasasecondarydomain.

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Figure 12.1. Percentageofinfrastructuresinotherprimarysectorsthatidentifiedenvironmentasasecondarysector.

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Case study: From the poles to the skies

TheNaturalEnvironmentResearchCouncil(NERC)ownsseveralresearchshipsthatsupportcomplex,multidisciplinaryresearchandincludestate-of-the-arttechnologyandinstrumentstomeetresearchneedsacrossalldisciplines. TheshipsenableoceanographicresearchinthemostextremeandremoteoceanicenvironmentsonEarth.OverfifteenyearsofNERCinvestmenthascreatedthelargestandmostdiversefleetofroboticresearchvehiclesinEurope,including10,000itemswithacollectivevalueestimated at£20million.NERCunmannedvehiclesgofurtheranddeeperthananycommercialormilitarycapability.

TheFacilityforAirborneAtmosphericMeasurements(FAAM)isEurope’slargestflyingatmosphericlaboratory,housedinamodifiedBAe146-301aircraft.Theaircraftcarriesalargeandversatilesuiteofinstrumentationtocharacteriseprocessesthroughoutthetroposphereuptoaround10kmaltitude.BarringAntarctica,itiscapableofoperatinganywhereintheworld.TheFAAMprovidestheUKatmosphericsciencecommunitywithaworld-classplatformforairborneresearch,tosupportresearchinareaslikeweather,climate,airqualityandEarthobservation.

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Theinfrastructureswithintheenvironmentsectorarebroad,diverseandgeographicallydistributedacrossthecountry.Seventy-eightpercentofenvironmentalinfrastructuresarelocatedoutsideofLondonandsouth-eastEngland.Nearlytwothirds(66%)aresinglesitefocused,withaquarterdistributedorgrouped.Asmallnumber(7%)identifyasahybrid/mixedmodel,forexample,theSvalbardIntegratedArctic EarthObservingSystemwhichhasphysical andvirtualassets.

TheenvironmentalscienceresearchsectorhasmanystrengthsindifferentplacesandorganisationsincludingHEIs,governmentdepartmentsandagencies,PSREssuchastheMetOfficeandUKResearchandInnovationanditsNERCresearchinstitutes.Non-governmentalorganisationshaveasmallyetinfluentialresearchportfolio.Regardingthelegalstructure,thevastmajority(88%)ofenvironmentalinfrastructuresarelocatedwithinalegalentity,suchasauniversityorresearchinstitute.Theremaininginfrastructuresareevenlysplitacrossshort-termexternallyfundedprojects,nationalandinternationallegalentities.

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Environmentalinfrastructuresareinhighdemandwithjustoverhalfreportinganincreaseindemandoverthelasttenyears,withanexpectedincreaseindemandinphysical,virtualandremoteaccessasshowninFigure12.2.

Environmentalinfrastructuresareoftenofnationalandinternationalimportanceanduniqueness.ThirtypercentofusersatUK-basedinfrastructureshavecomefromoutsidetheUK.Overhalf(56%)ofinfrastructuresstatedtheiruserswouldhavetotraveloutsideofthecountrytoaccessasimilarcapability.Mostimportantly,aquarter(26%)identifiedthattherewasnoothersimilarcapabilityintheworld;theseincluded

Birmingham’sInstituteofForestResearchFreeAirCarbonEnrichmentFacility(Figure12.3).

Theglobalchallengeswearefacingrequireglobalsolutions.Workinginaninternationalarenaandpartneringinternationallyisakeycharacteristicoftheenvironmentalsciencecommunityandtheinfrastructuresthatsupportit.Theoverwhelmingmajority(96%)ofenvironmentalinfrastructurescollaboratewithotherinfrastructuresandorganisationsand86%collaborateinternationally(Figure12.4).Thiswidecollaborativescopeisfurtherdemonstratedby95%ofinfrastructuresattractingusersfromothercountries.

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Figure 12.2. ExpectedchangeindemandforenvironmentalinfrastructuresforPhysical(outerring–P),Virtual(middlering–V)andRemoteaccess(innerring–R)overthenext5-10years.

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Figure 12.4. Numberofenvironmentalinfrastructuresthatcollaboratewithotherinfrastructuresandorganisationsnationallyandinternationally.

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Case study: Tackling the space weather threat

Geomagneticstormsarerapidlybecomingoneofthebiggestpotentialthreatstomodernsociety.Theycancauseseriousdamagetopowergrids,communicationssatellitesandothervitalinfrastructure.Thepotentialongoingcostsfromasingleseriouseventhavebeenestimatedatupto£1.3trillionayear.

EISCAT_3D,thenext-generationEuropeanincoherentscatterradarsystem,isaninternationalcollaborationthatwilldelivermoresophisticatedradarobservationstoimproveourunderstandingoftheEarth’satmosphereanditsinteractionwiththegeospaceenvironment,includingspaceweathermonitoringandforecasting.UKenvironmentalsciencehascontributed£6.2millionofthe€65millioncosttobuildEISCAT_3D.

C. Heinselman

Courtesy of The National Institute of Polar Research, Japan

Thishighlevelofattractionontheinternationalstageisduetoinfrastructuresofferingabetteroverallpackage,e.g.support(57%),auniquecapability(51%),beingpartofaninternationalcollaboration(54%)orbeinghigher-quality(41%).Furthermore,overaquarter(27%)expectthatthenumberofinternationalusersislikely toincrease.

Theenvironmentsectorhadthehighestnumberofinfrastructures(70%)withanexpectedoperationallifespanofovertwenty-fiveyears,comparedtotheaverageof60%.Continuityoflong-terminfrastructuresforsustainedobservationsandthecollectionoflong-termdatasetsisvitalforthesector,suchastheMetOfficeObservationsNetworkthathasbeeninoperationsince1853.Theclearmajorityofenvironmentalinfrastructures(92%)areinoperation,withtheremainderindevelopment(2%),design(3%)andimplementation(3%).

12.2 Impact and outcomes for theeconomy,industry andpolicymaking

Environmentalsciencestimulatescleangrowth,avoidscoststoallowindustrytoremainresilienttoriskandshocksandsupportseffectivepolicy-making.Environmentalinfrastructuresareassociatedwitheconomicactivitysuchaspublicpolicy,agriculture,miningandhealthservices(Figure12.5).Additionally,71%ofenvironmentalinfrastructuresworkdirectlywithUKbusinessesand59%directlycontributetoshapingpublicpolicyanddeliveringpublicservices.Overhalf(57%)provideresourcesand/orrelatedservicestothewidercommunityinadditiontoprovidingtheinfrastructureitself.

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Case study: Creating new insights by unlocking our geological past

TheNationalGeologicalRepository(NGR)includesthelargestcollectionofUKgeosciencesamples,with16millionspecimenscuratedoverthepasttwocenturies.Itincludesover23,000rockcoresfromboreholesandhydrocarbonwellsaroundtheUK,themajorBritishcollectionofrocksandover3millionmicro-andmacrofossils–allavailableforinspection.TheNGRcollectionsarebeingscannedanddigitisedandmadeavailableonline,includingover1.3millionscannedUKonshoreboreholerecords.TheNGRhasbeenused,forexample,byenergyfirmstoavoidunnecessarydrillingcostsofaround£12millionperwellandbyminingcompanieslookingfornewsourcesofcriticalmetals.

BOSCORFistheUKnationalrepositoryfordeepseasedimentcoresprovidingspecialistlong-termstorageandcurationforover2500sedimentcores.Thecollectionisgrowingby100-200coresperyearandincludescoresfromallmajoroceanbasins.BOSCORFprovidesresearcherswithaccesstothisessentialmarinecollectionandenablesscientiststocarryouthighimpactscience.

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Figure 12.5. Topeconomicsectorsthatenvironmentalinfrastructurescontributetoorworkwith(excludingresearchandeducation).



Agriculture38 (45%)

Fisheries 30 (36%)

Construction26 (31%)

Mining28 (33%)

Forestry24 (29%)


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Theenvironmentsectorusesinnovativeandworld-leadinginfrastructuretorespondrapidlytonaturalhazardsandemergencies.Infrastructureprovidesourscientists,techniciansandpartnerswiththetoolstopredict,manageriskandensurethat,intheUKandglobally,peopleandbusinesscanprosperinaresilient,productiveandhealthyenvironment.Thisisbecomingincreasinglyimportantasenvironmentalscienceinfrastructureprovidesthedata,insightsandmodellingtotheUKanditspartnerstofindenvironmentalsolutionssuchasthechallengespresentedbyclimatechange.

ApartnershipbetweentheUniversityofLeicesterandlocalbusinessessecuredwiderutilisationofspace-basedEarthobservation(EO)data,enablingfortySMEstoincreasetheirtotalGVAby£950,000withinfouryears.Thepartnershipachievedthisviatargetedinterventions,developmentofproductsandservicesandtrainingintheuseofEOdata,generating£2.9millionofinvestmentinthe EastMidlandseconomy.

Formorethanthirtyyearsmarineinfrastructureshaveunderpinnedpioneeringconservationbiologyresearchbyenvironmentalscientists,tosupporttheUKgovernment’sleadershiproleininfluencinginternationalpolicyanddeliveringenvironmentalbenefitsandincome

fromsustainablefisheries.BirdIslandandKingEdwardPointresearchstationsandtheRRSJamesClarkRossarecriticalinfrastructuresinAntarcticaandthesub-Antarctic.Theyhaveenabledcriticalexpertiseandevidencetobegatheredforinternationalpoliciesandagreementstoprotectandconservemarineandterrestrialecosystems,aswellastosustainablymanageSouthernOceanfisheries.ThishasresultedinalargeareaoftheRossSearegionbeingdesignatedaMarineProtectedAreaandthevirtualeliminationofseabirdmortalityassociatedwithfishing.

TheUK’senvironmentalinfrastructurealsoenableseconomic,societalandpolicybenefitsacrosstheglobe,deliveringagainstIntergovernmentalPanelonClimateChange(IPCC)commitmentsandtheSustainableDevelopmentGoals.Infrastructureprovidesresearcherswiththetoolstoproduceinnovativesolutionstochallengesallovertheworld.Forexample,environmentalscientistshaveusedweatherpredictionstoreducepovertyandsecurefarmerlivelihoodsinAfrica.Theseforecastshavedeliveredsignificantbenefitstogovernments,businesses,aidagenciesandcommunitiesbyimprovingnationalweatherservices,providingearlywarningofcropfailureandenablingpoorfarmerstotakeoutcommercialinsuranceagainstweathershocks.

Case study: Responding rapidly to emergencies

FollowingtheeruptionoftheEyjafjallajökullvolcanoinIcelandin2010,volcanicashdisruptedaviationonaglobalscalewithhugeeconomiclosses.MetOfficeinnovationsinashdispersionmodellingandforecasting,underpinnedbyFAAM,avoidedtheunnecessaryclosureofUKairspaceandsavedairlines£290millionperday.

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TropicalApplicationsofMeteorologyusingSATellitedata(TAMSAT)andground-basedobservations,forexample,recentlyenabledUS$2.8milliontobepaidtofarmersin370locationsinZambiafollowingaseveredryspell.ThefarmersarepartofamandatoryinsuranceschemeintroducedbytheZambiangovernmenttoprotectfarmersagainstextremeweatherevents,thelargestschemeofitskindinAfrica.

12.3 E-infrastructure and data needs of the sector

Tacklingenvironmentalchallengesrequiresinnovativewaysofmodelling,simulatingandobservingtheenvironment.Thereisanincreasingneedtomanagelarge,interoperabledatasets,whichcomewithchallengessuchasvariabledataquality.OftheUK’senvironmentalinfrastructures,72%haveasignificante-infrastructureand/ordatarequirementandtwothirdsarealsoassociatedwiththecomputationalande-infrastructuresector.Overthreequarters(76%)envisagede-infrastructureanddatabecomingmorerelevanttotheminthenext fivetotenyears.

Theenvironmentsectorhasaworld-leadingdataanalysisandstorageinfrastructureknownasJASMINandgloballycompetitiveHPCcapabilitiesthroughtheUK’snationalsupercomputerARCHER.JASMINisagloballyuniquedata-intensivesupercomputerforenvironmentalscienceandcurrentlysupportsover160scienceprojects.Itsusers’researchtopicsrangefromearthquakedetectionandoceanographytoairpollutionandclimatescience.JASMINhasmorethan44petabytesofavailablestorage,equivalenttostoringover10billionphotos.ThesectoralsobenefitsfromNEXCS,MONSooNanditssuccessorMonsoon2todeliversupercomputinginfrastructuretoenablecollaborationbetweenNERCandthe MetOfficeinclimateandweathermodelling. Itprovidesacommoncomputingplatform, post-processingcapability,afastdatalinkandaccesstodataarchives.

NERC-fundedresearchersattheUniversityofReadingworkedwiththeMetOfficetodevelopcomputermodelsthatcanidentify‘stingjet’airstreamsandpredictseverewindsseveraldaysinadvance.ThisenabledtheMetOfficetostrengthenitsseverewindwarningserviceanddeliverannualsavingsincluding:

Twenty-threelives:duetoworkbeingsuspendedonhighbuildingsinextremewinds

350,000tonnesofCO2:byreducingfuelneededforaircraftdiversions

£120million:byenablingairlinestoimproveaircraftrouting

£5million:fromemergencyservicesmakingmoreinformedresourcingdecisions

AmodeldevelopedbyNERC’sNationalCentreforAtmosphericScienceprovidesairportswithwarningsofseverewinds.Nowincorporated intoMetOfficeforecastingmodels,itsaves£1.25millionperyearfortheMinistryof DefenceintheFalklands,forinstance,byminimisingflightdiversions.

Case study: Early weather warnings save lives and reduce costs

National Oceanic and Atmospheric Administration

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Chapter 13: Energy sector

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EnergyresearchandinnovationinfrastructurescoverabroadrangeofR&D,fromunderpinningscienceinuniversitiesthroughtolargedemonstrationfacilities.Itencompassesadiverserangeofresearchareasthatcanbecategorisedasfollows:

Powergeneration

NuclearFusionandFission Renewablegeneration(wind,marine, wave,tidal,solarandgeothermal)

FossilFuels(oil,gasandcoal)

Energydistribution

Electricalpowernetworksystems Naturalgasdistributionnetworks Alternativeenergyvectors(hydrogenandfuelcells,alternativefuelsincludingbiofuels)

Enablingtechnologies

EnergyStorage Carboncaptureandstorage Energyefficiencyanddemandreduction(buildings,transportandindustry)

Wholeenergysystemsunderstanding.Includingenergydemand,policy andregulation

Energyresearchalsoincludessupportingtechnologiessuchaselectrochemistry,materialsscience,systemsengineering,robotics,remoteandautonomoussystemsandadvancedmanufacturing.Muchoftheunderpinningscienceforenergyresearchisundertakeninfacilitiesthatarecross-cuttinginnatureandwhichhavenotidentifiedenergyastheirprimarysector.ExamplesincludetheSirHenryRoyceInstitute,Diamond,NationalPhysicalLaboratoryinfrastructuresinthePS&EsectorandtheBritishGeologicalSurveyfacilitiesintheenvironmentsector.

EnergyR&DisastrategicpriorityfortheUKandisakeycomponentofthegovernment’sIndustrialStrategy1andCleanGrowthStrategy38. Thekeyhigh-levelchallengesforenergyR&DintheUKinclude:

Developmentoflowcarbon,secureandaffordableenergytechnologies

Transitionfromthecurrentfossilfuel basedenergysystemtoafuturelow carbonsystem

ntegrationofintermittentrenewableenergysourcesintotheenergysystem

Decarbonisingsub-sectorsofenergyincludingheat,transportandindustry

Developmentofenergystorageinalltheenergyvectorsincludingelectricity,gas,heatingandcooling

13.1 Current landscapeGiventhefocusedsubjectarea,theenergysectorconsistsofarelativelysmallgroupofdedicatedinfrastructures.Thirty-threeinfrastructuresidentifiedenergyastheirprimarysectorinthequestionnaireresponses.However,asnotedabove,asignificantnumberofinfrastructureswithinothersectorsprovidecrucialunderpinningresearchcapability.Forty-fourpercentofthe718non-energyinfrastructuresalsocoverenergyasapartoftheirremitandsupportunderpinningscienceforenergyR&D.Thisindicatesthatthereisastronglinkbetweenenergyandtheothersectors(Figure13.1),especiallythePS&E,computationalande-infrastructureandenvironmentsectors.

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Powergeneration

TheFloWaveOceanEnergyResearchFacilityisamarineenergyresearchfacilityconstructedforcutting-edgeacademicresearchintowaveandtidalcurrentinteractions.FloWaveisalsoacuttingedgetoolforcommercialdeveloperstoensuretheirtechnologiesandprojectsperform‘rightfirsttime’andarede-riskedasmuchaspracticalbeforecuttingsteelorgoingoffshore.

Energydistribution

TheUniversityofManchesterHighVoltageLaboratory(officiallycalledtheNationalGridPowerSystemsResearchCentre)isthehometoresearchfundedbyindustry,theUKgovernmentandtheEU.Themixtureofhighlyskilledresearchersandacademicsprovidetheedgeininnovativeandexperimentationconsultancythatisnotfoundinotherservices.Thelab,alongwithitstestfacilities,iscapableofworkingwithexistingutilitiesanddevelopmentcompaniesintestingandassessingequipmentathighvoltages.Thestaffarecapableofprovidingconsultancyfortheneedsoftoday’stransmissionanddistributionexpansionandinnovation.

Enablingtechnologies

TherecentlyfoundedFaradayInstitutionistheUK’sindependentinstituteforelectrochemicalenergystoragescienceandtechnology,supportingresearch,trainingandanalysis. TheFaradayInstitutionbringstogetherscientistsandindustrypartnersonresearchprojectstoreducebatterycost,weightandvolumetoimproveperformanceandreliabilityandtodevelopwhole-lifestrategiesfromminingtorecyclingtoseconduse.

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EnergyinfrastructuresaredistributedinallfourcountriesoftheUK,withparticularconcentrationsinsouthWales,ScotlandandcentralEngland.Oftheinfrastructuresidentifyingenergyastheirprimarysector,91%alsoidentifiedwithPS&Eand64%werealsorelevanttotheenvironmentsector.Forexample,energyistheprimarysectoroftheEdinburghCentreforCarbonInnovation(ECCI)andtheEastRidingofYorkshireCouncil(Ergo),buttheyalsoidentifystronglywithenvironmentaswell.TheSustainableProductEngineeringCentreforInnovativeFunctionalIndustrialCoatings(SPECIFIC)andNationalNuclearLaboratory(NNL)bothmentionedthatenergyistheirprimarysector,whilsttheyalsocoverPS&E.

Themajorityofenergyinfrastructures(82%)aresinglesitephysicalentities,whichagainisahigherpercentagethantheotherfivesectors.Manyofthesmaller,morehighlyfocusedfacilitiestendtobelocatedinuniversities,suchastheFloWaveOceanEnergyTestFacilityatEdinburghUniversity.Co-locatinginauniversityprovidesthesupportingscientificcapabilityinareassuchasmaterialsresearchthatunderpinthissector.

13.2 Recent investmentsManyoftheinfrastructuresintheenergysectorarerelativelynewwith81%oftheidentifiedinfrastructureshavingstartedoperations

withinthelastfifteenyears.ThisisduetotheincreasedinvestmentinenergyR&Dthathastakenplaceovertheperiod,investmentthathasbeenmadeinresponsetointernationallyrecognisedfuturecleanenergy39needs.Forexample,spendontheEPSRC-ledUKResearchandInnovationenergyprogrammehasincreasedfromaround£30millionperannumtoaround£180millionperannumsince2004.TheEnergyTechnologyInstitute(ETI)wascreatedin2008withaten-yearbudgetofupto£100millionperannumthatwas50:50public/privatefunded.AtthesametimetherehasbeenasignificantexpansioninenergyR&DsupportbyBEIS.RecentlytheUKgovernmenthaspledgedtodoubleenergyR&Dtoaround£400million perannumasdescribedintheMissionInnovationprogramme40.

Recentinvestmentsreflecttherelativeeconomicandpoliticalimportanceofdifferentenergytechnologies.Forexample,theexpansionofgeneratingcapacityforoffshorewindenergybetween2008and2018fromunder0.5GWtoover8GWofinstalledcapacityhasbeensupportedbysignificantinfrastructureinvestmentinOREbothpriortoandduringtheexpansion.FacilitiessuchastheORECatapult,theFlowaveandCOASTfacilitiesallcontributedtobuildingunderstandingofandovercomingtheengineeringchallengesassociatedwithplacinggenerationinfrastructureinthesea.

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Figure 13.1. Distributionofinfrastructuresfromtheotherfivesectorsthatidentifiedwithenergy.Identificationwasparticularlystronginthephysicalsciencesandengineering,environmentandcomputationalande-infrastructuresectors.

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Case study: Coastal, Ocean And Sediment Transport (COAST)

HousedintheMarineBuildingattheUniversityofPlymouth,theCOASTlaboratoryprovidesarangeofworld-classphysicalmodellingfacilities.Physicalmodelsarepowerfultoolsthatfacilitatetheunderstandingofthepotentialbehaviourandde-riskingofengineeringprojects.

Waves,currentsandwindaregeneratedatscalessuitableforresearch,designandoptimisationstudiesacrosstheocean,coastalandfluvialengineeringandphysicalsciencesectors.Recognisedasaninternationalcentreofexcellenceforresearch,developmentandteachinginthesefields,COAST’sclientsincludecentralandlocalUKGovernment,theEuropeanCommissionandinternationalfundingagencies,aswellasconsultants,contractorsanddevelopers.Sinceitsinceptionin2012,COASThasbecomealeadinglightintheglobaldrivetofurtherthelearninganddevelopmentofthenascentmarinerenewableenergysector,andisseatedattheheartofthecollaborativeSupergenOREHub.

MorerecentlytherehasbeensignificantinvestmentinnuclearfissionR&Dfacilities,mostlyinuniversitiesorbuildingonexistingcapabilityinNNL,SellafieldLtd,theDaltonCumbriaFacilityandUKAtomicEnergyAuthority(UKAEA)atCulham.ThisinvestmentisongoingandincludesrecentlyapprovedadditionalsupportfortheNationalNuclearUserFacility(NNUF)phase2expansion.ThisexpansionininfrastructureisinrecognitionthattheUKneedstodevelopandcommissionthenextgenerationsofnucleartechnologies.Inscaleanddiversitynuclearfacilitiesreflectgeneralenergyinfrastructure,withsomebeingdistributed,suchasNNUFandsomebeingsinglesitenationalcapability,suchasNNL.Facilitiesexistassingle-sitedeitherbecausetheydealwithhighlyspecificchallenges,suchhighlyactivematerialsatNNL,orbecausetheyserveaspecificmarketthatissufficientlylargetowarrantasingleenergyresearcharea.Wheredemandandexpertisearedistributed,distributedinfrastructurescanbemoreappropriatetoavoidhavingtorelocateandcentralisecapability,ortoavoidtheduplicationofcapability,e.g.NNUF.

NotalloftheenergyresearchinfrastructureisfocusedonmiddleorhighTechnologyReadinessLevels(TRLs)41.Forexample,theUKhasastrongtrackrecordinnuclearfusionresearch

andtheUKAEAfacilityatCulhamCentreforFusionEnergy(CCFE)hashostedtheJointEuropeanTorus(JET)andMegaAmpSphericalTokamak(MAST)facilitiessincetheearly1980s.TheworkundertakenatCCFEinvolvesabreadthofresearchincludingcutting-edgeplasmaphysicsandplasmacontrolandthedevelopmentofnewmaterials,roboticsandcontrolsystemsthatcanwithstandahighlyhostileoperatingenvironment.ItshouldbenotedthatthefusionfacilitiesareagoodexampleofinternationalfacilitycollaborationandplayauniqueroleincontributingtotheUK’sinternationalobligations(e.g.JET).Theycanalsoformanucleusofexpertisearoundwhichanationalprogrammecancoalesce,e.g.MAST.

InotherenergyareastheUKhasmoremodestcapabilities,withmostofthefacilitiesbeinglocatedinuniversities:

Solarenergy:theUKhasascientificleadinmanycutting-edgesolarenergytechnologies(thinfilmphotovoltaic(PV),organic/dyesensitisedPVandperovskitePV).TheSPECIFICInnovationandKnowledgeCentre,afacilityinPortTalbotandtheCentreforRenewableEnergySystemsTechnology(CREST)atLoughboroughUniversityarethetwosignificantcentresinsolarenergy

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Bioenergy:outsideuniversitiesthereislittleinfrastructureinbioenergy.TheUKdoeshavefacilitiesinagriculture,plantbreedingandgenomics,capturedintheenvironmentsector,butlittleontheconversiontechnologiestoturnbiomassintofuels

Power distribution:infrastructureismostlyfocusedonelectricaldistributionfacilitiesatStrathclydeandManchesteruniversities

HydrogenandFuelcells:researchismostlyundertakeninuniversities

Energysystemtransition:theUK’scapabilitiesaremodest

TheUKenergysystemisundergoingaslowbutfundamentaltransitionasincreasinglow-carbonenergysourcesarebroughtonline.Itisunclearexactlywhatthefutureenergylandscapewilllooklikeorwhatmixofenergysourceswillpredominate,butitisclearthatthefuturesystemwillbesmarterandmoreconnectedandhavetoco-ordinateawidevarietyofenergysources.Asaconsequence,thereisagrowinginfrastructurecapabilityinsmartmetering/systemsandtheassociateddata,modellingandsimulationthatisneededtounderstandtheimpactofthesechangesandtodevelopthetechnologyrequiredtoenablethem.MuchofthiscapabilityisinUKuniversities,whoarethedevelopersandcustodiansofmostoftheenergysystemmodels,butthereareincreasinglinksbetweentheacademiccapabilityandindustry,facilitatedbyinstitutionssuchastheEnergySystemsCatapult.

13.3 The role of data & e-infrastructure in the sector

Twothirdsofenergyinfrastructuresreporta‘significante-infrastructure/datarequirementorcomponent’.E-infrastructureisseenasnecessarybythesectortoaddressthechallengesofcapturingdata,undertakingcomplexmodellingandthesimulationofvarioussubsectors/subsystemswiththeaimofultimatelybeingabletosimulatetheentireenergysystem.E-infrastructureisalsoneededforappliedsolutionstorealsectorissues,suchasthereal-timemonitoringofremotefacilities(e.g.windfarms)whichisvaluableforperformancechecks,earlydetectionoffaultsanderrorsandensuringthesecurityofthesystemisintact.Threequartersofenergyinfrastructuresconsider

thate-infrastructureanddatawillbecomemorerelevantoverthenextfivetotenyears.

Intheenergysectordataareaparticularlyvaluableresourcethatcanbeusedtoinformmodels,improveaccuracyofforecastingandcostoptimisation,informpolicyinterventionsandhelpbusinessestodevelop.Thesedatacancomeinmanyforms,suchasindividualuserdata,weatherdataforpredictionofpeaksandtroughsinelectricityproduction,systemsperformanceandcontroldataneededformaintaininggridstabilityandmarketdataforensuringoptimumefficiencyforsuppliersandconsumers.Itisimportantthatresearchers,businessesandaggregatorshavesufficientaccesstodatatoenableinformeddecisions.Hencedataareavaluableassetandarelegallyprotectedbothascompanypropertyandthepropertyoftheindividualcustomer.

Infutureenergysystems,theintegrationofvariedandnewsourcesandtypesofdatamayposechallengesintermsofbothstorageandcoordinatedsecuritypolicy,whichmaybesolvedbyinvestinginthelinkbetweenthecomputationalande-infrastructureandenergysectors.Futureenergyinfrastructuresneedtobelinkeddigitallytogethertoenabletheexchangeofdata,modelsandresults–otherwisewholeorevenpartialenergysystemscannotbemodelledorcontrolled.E-infrastructurecanalsoenabledigitaltwinningtechnologydevelopmentfortheenergysectorusingasensor-enableddigitalreplicaoftheenergysystem.Thismayenhancethepotentialformulti-vectorandmulti-sectorenergyinfrastructureapplicationsbydevelopingjointenergy-computationalande-infrastructureinfrastructures.

13.4EnergyasakeyeconomicsectorEnergyisakeyeconomicsectorandassuchishighlyregulated.Almostnoenergygenerationtechnologiescanbeinstalledwithouteithercertificationofthetechnology(e.g.nuclear)and/orpermissionsforinstallation(e.g.offshorerenewables).Thismeansenergytechnologiesneedtobethoroughlyunderstoodbeforetheyareallowedtomarket,resultinginastrongdriverfortechnologydevelopment,testingandcertificationcapability.Hence,energyistheonlysectorwhereeveryinfrastructurehassignificantinvolvementwithbusinessacrosstheboard

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Figure 13.2. Distributionofenergyinfrastructuresonadiscovery-to-commercialisationspectrum.

0%

10%

20%

30%

40%

50%

60%

Mostly discovery More discovery Balanced More commercialisation

Figure 13.3. Topeightsectorsoftheeconomythatenergyinfrastructuresworkwithorcontributeto(excludingresearchandeducation).



Manufacturing: All other11 (34%)

Public Policy

11 (34%)


Manufacturing: Electronics10 (31%)

Construction

9 (28%)Manufacturing: Machinery

9 (28%)

andithasthehighestskewinoutputtowardscommercialisation(Figure13.2).

Energyinfrastructuresaremainlyseenasimportantbytheutilitycompaniesandtheenergysupplychain(Figure13.3).Othereconomysectorsthatenergyinfrastructureshaveastrongrelevancetoincludepublicpolicy,transportation(automotive,aeronautical),manufacturing,instrumentationandconstruction.ThisemphasisesthatenergyinfrastructuresmakeawidebreadthofeconomiccontributionsandplayapivotalroleinthereductionofcarbonemissionsacrosstheUKeconomyalmostregardlessofsector.

WhilemostR&D-focusedinfrastructureshavebeenconstructedandoperatedusingpublicfunding,themajorityofdevelopment–anddeployment-focusedinfrastructuresareboth

public-andindustry-funded.TheyrepresentasharedorpooledresourcethatisavailabletomultipleindustriesandacademiaandthatdrawsonUKacademicexpertise.Whereinfrastructuresarecost-anduse-effectiveforindustrytobuildthemselvestheydoso,suchastheIntegratedTransportElectricityandGasResearchLaboratoryInTEGRel42,whichisledbyNorthernGasNetworksandisinpartnershipwithNorthernPowergridandNewcastleUniversity.Thispublic-privatefundingmodelisparticularlyevidentwheretherearemorenascentmarkets,whichrequiregovernmentsupportforpre-commercialactivitytoproveandde-risknewtechnology.Thisdual-supportmodelishighlydesirableasindustryisfacedwithappliedproblemsthattheacademicresearchbaseiswellplacedtohelpsolve,whileacademiagainsaccesstouniquechallengesthatcanpushthefrontiersofscience.

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Case study: Fusion energy infrastructures at UKAEA

UKAEA’scampusatCulhaminOxfordshireisoneoftheworld’sleadingcollectionsoffusionenergyresearchinfrastructures.ItsmainmissionistoleadthecommercialdevelopmentoffusionpowerandrelatedtechnologyandpositiontheUKasaleaderinsustainablenuclearenergy.UKAEAatCulhamhousesanumberofenergyinfrastructures.

JET atCulhamistheworld’slargestmagneticfusionexperimentandisalsothelargestEUfacilityintheUK.Itexploresthepotentialoffusionasasourceofenergyusingatokamak,aninfrastructurethatholdshotplasmainatightmagneticfield.Asatomsfuse,energyisreleasedandabsorbedasheatinthewallsofthevessel.

MASTistheUK’sfusionenergyexperiment.MASTholdsplasmainatightermagneticfieldthanconventionaltokamakslikeJETbyformingasphereshapedplasmaratherthanadoughnut.Thishasthepotentialtoproducemoreeconomicalandefficientfusionpower.

The Materials Research Facility (MRF) hasbeenestablishedtoanalysematerialpropertiesinsupportofbothfissionandfusionresearch.ItispartoftheNNUFinitiative,launchedbythegovernmentandfundedbyEPSRC,tosetupamulti-sitefacilitygivingacademiaandindustryaccesstointernationallyleadingexperimentalequipment.TheMRFisalsopartoftheSirHenryRoyceInstituteforAdvancedMaterials.

EURO

fusi

on

Mon

ty R

akus

enU

KAEA

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Chapter 14: Computational and e-infrastructure sector

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Theterme-infrastructurecoversallinfrastructurethatenablesdigital/computationalresearch.Itshouldberegardedas‘scientificinstrumentation’.ThebuildingblocksareshowninTable8.1.

Table8.1.Thebuildingblocksofe-infrastructure

Networks International/national(GÉANTandJanet),local

Software Tools(operatingsystems,digitalandsoftwarelibraries,accessmanagementsystemsetc.)

Applicationcodes(modelling,simulation,dataanalytics)

Computers Supercomputers

High-throughputcomputersfordataanalysis

Data infrastructure Infrastructureformoving,storing,analysing,visualisingandarchivingdata

Access mechanisms Cloudtechnologies

Accessmanagementandidentitymanagementtechnologies

Computationande-infrastructureisanimportantunderpinningcomponentoftheresearchecosystemacrossUKResearchandInnovationandiscriticaltotheoperationsofanumberofpublicsectorbodiessuchastheMetOffice.JiscistheUK’sproviderofdigitalsolutionstoresearchandeducation.ThisincludesthesuperfastJanetnetwork,Eduroam,domainregistries,digitalcontent,trainingandinfrastructure.

ThecurrentUKe-infrastructureecosystemhasevolvedovermanyyearsratherthanbeing‘designed’.Thisreflectsthediversityofthecommunitiessupportedandtherangeoffundingsourcesandmechanisms.Overthelastfiveyearsastrongcultureofcollaborationhasbeendevelopedamongstkeye-infrastructuresacrossallfields.TheUKisinagoodpositiontobuildonthesefoundationsandexplorethescopeforincreasedcollaborationandsharingofe-infrastructureinthefuture,includinglinkingintoglobalinitiativessuchastheEuropeanOpenScienceCloud(EOSC)andEuroHPC.

Seventy-twopercentofinfrastructuresfromothersectorsreportedarequirementfore-infrastructure.Itislikelythatthisunderrepresentstheactualrequirement becausecomputationalanddigitalapproachesarebecomingubiquitousacrossallfields ofresearch.

14.1 Current landscapeThecomputationalande-infrastructuresectorhasstrengthindiversity,reflectingthediversityofresearchneeds.Thisdegreeofdiversitydefieseasycategorisation,butFigure14.1attemptstocaptureit.

Atthecentreofcomputationalande-infrastructurelandscapearethepeople:boththeacademicandindustrialusers,andtheexpertswhoruntheservices.TheinfrastructureisdependentontheJanetnetworktoprovideaccessroutesandthetechnologyformovingdata.Akeyelementisthesoftwareinfrastructure.Asignificantmajorityofresearchacrossalldisciplinesreliesonspecialistresearchsoftwareformodelling,simulationandanalysis.Softwareiswheremuchintellectualproperty,knowledgeandunderstandingresidesandthisiswhysoftwarehassuchlongevity.Peoplereplacetheircomputeanddatahardware,butdonotdisposeoftheircodes.Softwareshouldbeconsideredaresearchoutputinitsownrightandformskeyinfrastructure.Finally,therearethediversehardwarecomponents,suchascomputinganddataplatforms,tailoredtomeettheresearchandinnovationrequirementsofusers.

100

Figure14.1.TheUK’scurrentnationalresearchandinnovatione-infrastructureecosystem.

Theuseofe-infrastructureissignificantacrossallsectors(Figure14.2).Itisusedasatoolin59%ofinfrastructuresthatdidnotidentifye-infrastructureastheirprimarysector.Itistheprimarydisciplineof17%ofBH&Finfrastructuresandaround10%ofPS&E,SSAHandenvironmentinfrastructures.

>100,00Academic

& IndustrialUsers

JANET Network

Access

IRIS

Data platforms fortranslational focus of

social science, arts and humanities

CCPs

OPERATIONAL RESEARCH - Supercomputing

GEN

ERIC

SPECIFIC

- data-intensive computing GENERIC SPECIFIC -

High-th

roug

hput

com

putin

g

Software Infrastructure & Projects

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Case study: UK Data Service (UKDS) and retirement income

TheUKDSisanESRC-fundedinfrastructurepartnershipbetweenbetweenEssex,Manchester,EdinburghandSouthamptonuniversities,UniversityCollegeLondon(UCL)andJisc.Itprovidestraining,supportservicesandaccesstomajorUKgovernment-sponsoredsurveys,cross-nationalsurveys,longitudinalstudies,UKcensusdata,internationalmacro-data,andbusinessandqualitativedata.

ResearchbytheResolutionFoundationusedacombinationofdataresourcesfromtheUKDSandOfficeforNationalStatistics(ONS)toassessfuturepensionerincome.Fortheiranalysisofoutcomesforrecentcohortsofpensioners,thefoundationuseddatafromtheBritishHouseholdPanelSurveyandUnderstandingSociety,itssuccessor.Forward-lookingprojectionsusedtwoONSsurveys:theNewEarningsSurveyandtheAnnualSurveyofHoursandEarnings.

Theresearchersfoundthatfuturepensionersshouldexperiencesimilarlevelsofearningsreplacementadequacyassumingretirementatstatepensionage,comparedwithrecentretirees.Theanalysisshowsthatthepoliciesbeingimplementedarepreventingdeteriorationinoutcomesacrossfuturecohortsofpensioners,butthatambitionsforearningsreplacementadequacyappeartoremainquitefaroutofreach.

TheresultsinformedthediscussionwithintheDepartmentforWorkandPensions(DWP)policypaperAutomaticEnrolmentReview2017:MaintainingtheMomentum.DWPwilllowertheageatwhichemployeesarerequiredtobeauto-enrolledinworkplacepensionsfromtwenty-twotoeighteen,aswellaswideningeligibilitytoworkersintheUKwhoearnlessthan£5876peryear.

0% 20% 40% 60% 80% 100%

BH&F

PS&E

SSAH

Energy

ENV

E-INF

Not used Primary discipline Used as a tool

Figure 14.2.E-infrastructureusagebyinfrastructuresinsectorsthatdidnotidentifycomputationalande-infrastructureastheirprimarysector.

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Tounderstandthediversity,complexityandtypesofe-infrastructuresweconductedasecondaryclassificationofinfrastructures,dividingthemintothefollowing:

E-infrastructurefacilities(e.g.ARCHER,DistributedResearchusingAdvancedComputing-DiRAC)

Experimentalfacilitieswithamajorrequirementfore-infrastructuretosupporttheresearchthatfacilityusersarecarryingout(e.g.Diamond,SquareKilometreArray)

Datafacilitiesandresourceswithamajorrequirementfore-infrastructuretosupporttheresearchthatfacilityusersarecarryingout(e.g.JASMIN,UKDS)

Researchcentres/institutesthatmayhavetheirowne-infrastructuretosupportresearchprogrammes,butwhichmayrequireaccesstothethreeclassesofe-infrastructureabove(e.g.EarlhamInstitute,HealthDataResearchUK)

Themajorityofinfrastructures(66%)fallintothefourthofthesecategories,aroundaquarter(24%)fallintoeitherthesecondorthirdcategoryandtherest(10%)fallintothefirstcategory.

Unlikesectorsdominatedbylarge,physicalinfrastructuresthatarevisitedinperson,manye-infrastructuresareaccessedremotelyovernetworksand,fromauser-accesspointof

view,theirphysicallocationislessinformation.However,forsomeoftheexperimentalfacilitiesthathaveane-infrastructurerequirement,userswouldstillbelikelytoattendinperson.

Thehardwareunderlyinge-infrastructurechangesrapidly,withmajorrefreshesneededonatimescaleofthreetofiveyears.Thisisevidencedbytherecentcapitalinvestmentsmadeinthissector(Figure14.3).Thismayhelpexplainwhyalargerproportionthaninothersectorsarereliantonshort-termfunding(28%versusanaverageof14%).However,manyinfrastructuresinthissectordohaveasignificantlifespan(Figure14.4).Itislikelythatthee-infrastructurecapabilityitselfmayhavealonglifespan,butthetechnologythatitreliesonwillneedregularreplacement.Forinstance,Diamondwillhaveadecades-longlifespanbutduringthattimewillneedtoupgradeandreplaceitsdatastorage,softwareandresearchcomputingfordataanalysisanditsnetworkcapacity.

TheResearchCouncilsperformedadetailedquestionnaireofe-infrastructurefacilitiesin2017andthereportgeneratedfromitcontainsconsiderableinformationabouthardware,software,servicesandpeople43.FromthatquestionnaireitwasapparentthatHEIsremainthemainproviderofdataandcomputeservicestothenationale-infrastructureecosystem, withthirty-sixHEIsprovidingnationalor regionalservices.

0

50

100

150

200

250

2011 2012 2013 2014 2015 2016 2017 2018

Mill

ions

(£)

Figure 14.3. Recentcapitalinvestmentsmadeine-infrastructureaccessibletothewideracademiccommunity.InvestmentsarelargelyaimedatmaintenanceofexistingcapabilitywiththeexceptionoffundingofARCHER2in2017.

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14.2E-infrastructure,data and innovation

Dataareoftenkeytoinnovation.TheHartreeCentreisanincreasinglyimportantinfrastructureforUKindustryandacentreofexcellenceintermsofhowtoapplyHPC,cognitivecomputingand‘bigdata’expertisetoawidevarietyofindustrialchallenges.ContinuingtodevelopthiscollaborativeapproachwillboosttheUK’scompetitiveedgeandhelpdelivereconomicgrowthandjobcreation.

WhilstHartreeistheonlyinfrastructuredirectlytargetedatindustry,thereisconsiderableindustrialusageofothere-infrastructuresviaeitheracademic/industrialcollaborationsordirectusage.Seventy-onepercentofe-infrastructuresstatedthatatleastsomeoftheirworkisinformedbytheneedsofbusinesses.Forexample,ARCHERcollaborated

withRolls-Roycetodemonstratethescalingofmodellingacrossmanyapplications.However,e-infrastructuresgenerallysupportresearchatthediscoveryendofthespectrum(57%)orhaveabalancedportfolio(37%).

Thetopeconomicsectorsthate-infrastructurescontributetoinadditiontoresearchandeducationincludecommunications,computing,healthservices,pharmaceuticalmanufacturing,publicpolicyandtransportation(Figure14.5).WhatisnotapparentfromFigure14.5isthedepthanddiversityofeconomicsectorsthataresupportedbye-infrastructures.Eache-infrastructuresupportsanaverageofseventeeneconomicsectors,fargreaterthananyotherdomainsectorandeverysectoroftheeconomyissupportedbyatleastaquarterofalle-infrastructures.

Figure 14.5. Topsectorsofeconomythatcomputationalande-infrastructureinfrastructurescontributeto(excludingresearchandeducation).

16%

26%

15%

43% Up to 5 years

5-15 years

15-25 years

Over 25 years

Figure 14.4. Expectedoperatinglifespanofcomputationalande-infrastructures.Overhalfhaveanexpectedoperatinglifespanexceedingfifteenyears.

Services: Health49 (77%)


50 (78%)Communcations & information

11 (34%)

Manufacturing: Pharmaceutical

37 (58%)



Utilities: Energy

9 (28%)Manufacturing: Electronics

31 (48%)

Case study: Rolls-Royce and ARCHER

Rolls-RoyceusethenationalHPCservice,ARCHER,totestthescalingoftheircodesforavarietyofapplications:fluiddynamics,noise,combustionandastructuralmodelofafullenginetestrig.

Rolls-Roycearemajorplayersintheaeronauticalsectorwithanannualspendof£800millionandatotalimpactonUKGrossDomesticProduct(GDP)ofover£10.2billion.ScalingisimportanttoRolls-Roycetoensurethey

canmeettheirdesigntimescalesandtheywereabletorunamuchlargerscaleonARCHER.AccessdemonstratedtheartofwhatwaspossibleforRolls-Royceandhassettheircomputationalscienceandengineeringroadmapforthecomingtwotothreeyears.

Rolls

-Roy

ce

Case study: The Materials and Molecular Modelling Hub

Thishubprovidesresearcherscarryingoutresearchintomaterialswithaccesstoastate-of-the-artHPCfacilitynamedThomasafterBritishphysicistThomasYoung.Modellingandsimulationenablefundamentalinsightsintotheprocessesandmechanismsthatunderliephysicalphenomenaandhasbecomeanindispensableelementofcontemporarymaterialsresearch.

Thefacilitywasestablishedin2017.ItisapartnershipbetweenEPSRCandaconsortiumof

universitypartners:ImperialCollege,Kent,KingsCollegeLondon,Oxford,Cambridge,QueenMary,Queen’sUniversityBelfast,SouthamptonandUCL.Aswellasaccesstothesupercomputer,thefacilityalsoofferstrainingactivitiesandskillsdevelopment,pluscommunity-building.

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Annex A: Definition of research and innovation infrastructure used within this programme

Researchandinnovationinfrastructuresarediverse.TheprogrammehasdrawnonthedefinitionsusedbyESFRI44andtheHorizon2020ResearchInfrastructureProgramme11:

facilities, resources and services that are used by the research and innovation communities to conduct research and foster innovation in their

fields. They include: major scientific equipment (or sets of instruments), knowledge-based resources such as collections, archives and scientific data, e-infrastructures, such as data and computing

systems and communication networks, and any other tools that are essential to achieve excellence

in research and innovation.

Infrastructurescanbesingle-sited(asingleresourceatasinglelocation),distributed(anetworkofdistributedresources),orvirtual(theserviceisprovidedelectronically)butareusuallyaccessedthroughasingleentrypoint.

Thisprogrammefocusesonmajorresearchandinnovationinfrastructuressupportedthroughgovernmentandaccessibletoallusersfromacademiaandindustry.Ingeneralthismeans:

Evidenceofsustainedand/orsubstantialUKpublicfundingcommitment(tobuild,operate,upgrade,decommission)isrequired(canbethroughmultiplechannels)

Privatesectororganisationsandinstitutionsfundedbyandforuseofasingleresearchestablishment(e.g.asingleuniversityorPSRE)willbetreatedasoutofscope

MajorresearchandinnovationinfrastructureswithinPSREs,UKuniversitiesorEuropeanandinternationalorganisationsthatarevitalfortheUKresearchandinnovationcommunitywouldbewithinscope

Requirement1:purposeAninfrastructuremustprovideanessentialplatformtoconductorfacilitateexcellent researchandinnovationthatbenefitstheUK,asdemonstratedbyindependentassessmentsuchaspeerreview.Thiscouldbethroughprovisionofequipment,facilities,analyticalservices,dataandunderpinninginfrastructure.Thismightbeencapsulatedwithinafacility,researchandinnovationorganisationorpartofanorganisation.

Theinfrastructureshouldberegardedandoperatedasastrategiccapabilityenablingcollaboration,supportingthemeetingofspecialistandtechnicalneedsandprovidinginnovationinservicesupport(e.g.regulatorycompliance)whichleadstoefficiencyofoperationandreducedduplication(e.g.uniquecriticalmass,coordination,scheduling).

in scope out of scope

Accessmustbeopentorelevant, publicly-fundedUKusercommunities beyondtheowner/operator

Accessibletoonlyoneoraverylimitednumberofresearchersororganisations

Publicly-fundedusersmayincludeHEIs,institutes,PSREs,researchandtechnologyorganisationsandotherresearchand innovationorganisations

Usedonlybyprivately-fundedR&D (e.g.industry)

Accessmayextendtoprivateor charitableusers(e.g.industry),inaddition topublicly-fundedusers

AccessmayincludeinternationalusersofUKfacilitiesandUKusersofinternationalfacilities

Accessmaybemanaged,e.g.throughuserregistration,fees,competition,meritreview,conditions,security;oritmaybeunmanaged

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Requirement2:accessibilityAninfrastructuremustprovideaccess,resourcesorrelatedservicestothewider,UKresearch and innovation communityoutsidetheinfrastructureinstitutionitself.

Requirement3:scaleandlongevityAninfrastructuremusthavesomedegreeofstrategic,internationalornationalimportance.Someinfrastructureswhicharecurrentlyregionallyimportantbutinkeyareasofemergingcapabilitymightalsobecaptured.

Aninfrastructureshouldbe: AssessedascriticalforUKresearchandinnovationexcellenceinoneormoresectors(consideredatfrontierofknowledge,addressingthemostpressingchallenges,demonstrableUKleadership,cutting-edgequality,importanceandrelevancetooneormorefields)

AssessedasbeneficialforUKresearchandinnovationimpact.Thiswouldincluderelevanceandalignmentwithgovernmenteconomicandsocietalchallengesandpriorities.Evidenceofimportancetotheusercommunitythrougharangeofpathwaysincludesleverageofco-funding,roleaninfrastructureplaysbothwithinthelocaleconomyandatanationallevel

Inadditionthereisanimplicitexpectation thatshort-term,focusedprojectswithoutlong-termsustainability(existingorplannedandrelativetoassetandtechnologylifecycles)wouldnotbewithinscope.

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Annex B: MethodologyThisfinalanalysisoftheUK’scurrentresearchandinnovationinfrastructureshasdrawn heavilyondatacollectedthroughtwoquestionnairesthatreachedover950existinginfrastructures.Thisannexfirstcoversthecontentofthequestionnaires,theapproachtakentoreachtargetrespondentsandresponserates.Itincludestheapproachtakentoassessandfillanygapsinthedatasetandimplement aclassificationsframeworktosupportthe morerobustanalysispresentedhereinthefinalreport.Thisisfollowedbyasectioncoveringcaveatsonthedatacollectedplushowbest useofavaluablethoughimperfectdataset hasbeenmade.

Throughouttheinitialanalysisadditionalinformationgatheredthroughworkshopsandstakeholderinterviews,plusreviewsofexistingreports,hasbeenusedtosense-checkmessagesfromthedataanalysisandtoprovidesupplementaryinsightontheinfrastructurelandscape.Thisannexdoesnotgointodetail onthissupportingwork.

Questionnaire approachQuestionnairesoneandtwowereconductedduringspring/summer2018.Thegap-fillingquestionnairewasconductedduringwinter 2018andwasanamalgamationofquestionnairesoneandtwo.

Broadly,thefirstquestionnaireasked questionstogatherawiderangeofdescriptiveinformationoninfrastructures.Thesecondquestionnairesoughttodigdeeperinasmallnumberofkeyareasandgathertheviewsofinfrastructuresonfuturetrends,aswellascurrent/futurebarrierstomaximisingqualityoutputs.Thefollowingtableliststhetopicscoveredbythequestionnaires.

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Questionnaire one Questionnaire two

Backgroundinformation: Descriptionoftheinfrastructure Location Configuration(singlesite/distributed/virtual) Strategicplans

Legalnature: Legalnatureofthoseinfrastructuresestablished asnationallegalentities

Lifecyclestage: Stageofinfrastructureinlifecycle Firstyearofoperations Lifespan

Domain/sector: RelevanceofRoadmapsectors RelevanceofsubdisciplineswithinRoadmapsectors Relevanceofe-infrastructure(disciplineofinfrastructure versususedastool)

Expectedgrowthofrelevanceofe-infrastructure

Domain/sector: Roadmapsectorscovered Primarysector Significanceofe-infrastructure Sectorsofeconomysupported

Work with others outside academia: Contributiontopublicpolicymaking/deliveryofpublicservices Workwithbusinesses,charitiesandthenon-academicpublicsectorathomeandabroad

Scope & collaboration: Scope/reachofinfrastructure Extentofaccesstoexternalusers Provisionofresources/servicesto widercommunity

Collaborationwithorganisations,nationally andinternationally

Topcollaborators Extentofdiscoveryversuscommercial focusedresearch

Extentofworkwithbusiness

Position in landscape: AccesstoUKusers Easeofsubstitutiontoalternativeinfrastructures ComplementaryinfrastructuresintheUKandabroad AttractionofusersbasedoutsideoftheUK

Users: Howusernumbersaremeasured Numberofusers Whereusersarefrom

Costs and decision points: Majordecisionpointsinthenextfiveyears Directandindirectfundingfromindustry,charityand othernon-governmentorganisations

Potentialforleveragingnon-governmentcontributions Viewsofwhethersourcesoffundingwillchange

Capacity: Howcapacityismeasured Percentageofcapacityused Targetcapacityuse

Reviews and evaluations: Whetherinfrastructurepeerreviewsusers Independentreviewsofinfrastructures

Costs: Establishmentcosts Annualcostsofoperations PrimaryUKpublicfundingsource Dependenceonpublicfinance Whetherinfrastructuretheresultofa public-privatepartnership

Future trends: Technologicaldrivers/trendsimpactinginfrastructurein mediumterm

Scientific/researchdrivers/trendsimpactinginfrastructureinmediumterm

Societaldrivers/trendsimpactinginfrastructureinmediumterm Possibleevolutionofinfrastructurestoaccountfordrivers/trends Barrierstomaximisingqualityoutputsnowandinmediumterm Numberoffutureyearscapacity/capabilityneedsconsideredfor Trendindemandoverlasttenyears Expectedgrowthofinternationalusersrelativetonationalusers

Staffing: Headcount StafffromUKandabroad Femalestaffpercentage Black,Asianandminorityethnicstaffpercentage Numberofstudents

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Targetrespondentsand response ratesThetargetaudienceforthefirstquestionnairewasallUKinfrastructuresandUKResearchandInnovationundertookextensivepreparatoryworktoidentifyasmanyaspossibleandtoestablishcontacts.Alistofalmost700infrastructureswithcontactswasdevelopedinconsultationwithsectorexperts,governmentdepartments,thecross-governmentanalystnetworkandtheDevolvedAdministrations.

Theseinfrastructureswereeachinvitedtocompletethefirstquestionnaire.InparallelthequestionnairewaspromotedtoallHEIvicechancellorsbyResearchEnglandandtheirdevolvedequivalentsforwidercoverageandtoreachinfrastructureswithunknowncontacts,plushithertounknowninfrastructures.AlinkwasalsoplacedontheUKResearchandInnovationwebsiteandpromotedbythenationalacademies,theAssociationofInnovation,ResearchandTechnologyOrganisations(AIRTO)andothers.

Thefirstquestionnairewascompletedby835entities–325(47%)ofthe697infrastructuresdirectlyinvitedtoparticipatecompletedthequestionnaire,whilst510responsescameaboutfromthewiderpromotionalwork.Ofthe835responses,712fulfilledthecriteriaofbeinganationalorinternationalinfrastructureandforty-threeresponsesrepresentedregionalinfrastructures.Thesecondquestionnairewassenttoeveryonewhocompletedthefirstquestionnaire.Theresponserateforthe712national/internationalinfrastructuresfromthefirstquestionnairewas83%.

Datafromthefirstandsecondquestionnairewereusedforthe‘InitialAnalysisreport7’,publishedinNovember2018.OneofthereasonsfortheInitialAnalysisreportwastostimulatefurtherengagementwiththecommunityandtofillthegapsincompletionwithsomesectors;forthispurposeagap-filingquestionnairewasconductedinWinter2018.Aswellasengagingnewinfrastructures,institutionswhichhadcompletedthefirstandsecondquestionnaireswereidentifiedandinvitedtocompletethegap-fillingquestionnairefortheirinfrastructures.ThisensuredthatweincludeddataattheappropriatelevelaccordingtotheclassificationdevelopedandpresentedintheInitialAnalysisreportanddidnotexcluderesponsesthatwereotherwiseimportanttotheprogramme.Thegap-fillingquestionnairereceivedafurther110responsesleadingtoadatasetcovering945infrastructures.

ClassificationframeworkAllquestionnaireresponseswereindependentlyclassifiedaccordingtotwomeasures:organisationallevel(e.g.institution,sub-node)anduniquenessofcapability.Questionnairedata,independentdeskstudiesandverificationfromsectorexpertswereusedtoinformandvalidatetheclassification.Thiswasdonetoallowamorenuancedandrobustapproachtodataanalysis.ThoseinscopearehighlightedinTablesB2andB3.

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Cluster outofscope

Aclusterofinstitutionswithassociatedinfrastructures,suchasacampus,scienceparkoruniversityconsortium,suchasthe N8groupofuniversities

Institution outofscope

Aninstitutionwhosecorepurposeisgreaterthantooperateasingleinfrastructure.Eithertheinstitutionhousesmultipleinfrastructuresand/oritperformssignificantotherfunctions,suchaspublicengagement.Examplesincludeuniversitiesandnationallabs

Coordinatinginfrastructureinscope

Aninfrastructureinitsownrightthatcoordinatesotherinfrastructureswithinit.AnexamplewouldbetheCentreforLongitudinalStudiesthatalsohostsfourdistinctcohortinfrastructures.Itdiffersfromaninstitutioninthatitdoesnotperformsignificantotherfunctions.ManydistributedESFRIprojectsarecoordinatinginfrastructures

Infrastructureinscope

Facilities,resourcesandservicesthatareusedbytheresearchandinnovationcommunitiestoconductresearchandfosterinnovationintheirfieldsandprovideadistinctcapability

Infrastructurescanbephysicalorvirtualresources,orthefacilities,instruments,toolsandtechniquesthatsupportthem.Theycanbelocatedatasinglesite,mobileordistributedacrossmanyplacesAsingleinfrastructurecanalsobeaninstitution,e.g.Diamond.Itwouldbecategorisedasinfrastructureifitdidnotperformsignificantotherfunctions(e.g.teaching,outreach)

National Node inscope

Nationalcomponentpartsdistributedinternationalinfrastructures

Sub-nodes:RegionalNodeoutofscope

Regionalcomponentpartsofdistributednationalor internationalinfrastructures

Local Nodeoutofscope

Localcomponentpartsofnationalorinternationalinfrastructures

Table B2.Organisationallevelofentitiesidentifiedthroughquestionnaires.

Internationalinscope

OnlycapabilityintheUK.Othersimilarcapabilitiesmayexistinothercountriesoritmaybeoneofakindglobally.Differsfromanationalinfrastructureinthatithasaninternationalreputation,withstronginternationaldraw

National inscope

OneofonlyahandfulofcapabilitiesintheUKortheonlyoneintheUK.Differsfromaninternationalcapabilitybybeingmorenationallyfocused,althoughitmayhavesomeinternationalusersorcollaborateinternationally

Regionalsectoranalysesonly

InfrastructurecapabilityreplicatedintheUKataregionallevel.It’slikelytobetheonlyoneintheregion,oroneofasmallnumberintheUK

Localoutofscope

Infrastructureisoneofseveralsimilarcapabilitiesinaregion(regionssuchasWalesorinthesouth-eastofEngland).Outofscopeforallanalyses

Table B3. Capabilityscopeofentitiesidentifiedthroughquestionnaires.

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CaveatsonquestionnairedataNoquestionnairewillevercapturethetotalityofresearchandinnovationinfrastructuresinthelandscape.Someinfrastructuresmayhavemissedthecommunicationsaltogether.Forsomesectors,suchasthesocialsciences,artsandhumanities,theconceptofaninfrastructureisrecentandlessembedded,riskingnon-participationasaresultofalackofself-identification.Someofthelargestinfrastructuresmayhaveconsideredthattheyweresowellunderstoodtherewasnoneedtocompletethequestionnaire.Wemitigatedthesebiasesbycross-referencingourengagementagainstlistingssuchasESFRI24andMERIL45.

Thereisnotanevenspreadofinfrastructuresacrossthesixbroadresearchandinnovationsectors.Anyoverarchinganalysesofthelandscapewillbedrivenbysectorswiththelargestnumbersofinfrastructures(i.e.physicalsciencesandengineeringandbiologicalsciences,healthandfood)andwhilstthisgivesthecorrectoverallpictureitshouldberememberedthatitmaynotberepresentativeofaparticularsector.Intermsofcross-sectorcomparisons,forquestionswithsmallsamplesizeswehavenotdrawnconclusionsfromsmalldifferencesinthedata.

Webelievethatwhilstspecificgapsmayexistinthequestionnairedatafrommissingindividualinfrastructures,thereisrepresentativecoverageoverall.GapsidentifiedafterpublicationoftheInitialAnalysisreportthroughsectoranalysisandstakeholderinputwereaddressed,particularlyinthespaceandclinicaldisciplineareas.

Anothersourceofpotentialbiasarisesfromvariationininfrastructures’scaleandpositionintheorganisationaltopology.Intermsofscaletherecouldbeabiasifequalweightingwasgiventoeachinfrastructure,forexample

whetheritisthenationalarchive(e.g.theBritishLibrary)orasmallerspecialistone.SincetheInitialAnalysiswaspublishedwedevelopedandappliedtheorganisationalandcapabilitycategorisationpresentedinAnnexBtocontrolforthisandremoveentriesthatwereoutofscopeforthisprogramme. Thequalityofdatageneratedbyquestionnairescanbevariable.Questionnairesaresubjecttodifferencesinunderstandingandinterpretation,especiallywhenlanguageandterminologydiffernaturallybetweenthebroadsectorswetargeted.Tocaptureasbroadapictureaspossible,somequestionswereoptionalleadingtovariationinsamplesizesandnoteveryquestioncouldbeposedinawaythatwaseasytoanalyse.Additionally,whilstwewerecarefulinclarifyingourcriteriaforengagement,wereceivedcompletionsfrominfrastructuresthatdidnotfittheseorthatwerefromacampusoraninstitutionratherthanfromtheinfrastructureswithinthem.

Wecontrolledqualityinanumberofways.Everyentrywasreadandassessedagainstourcriteria(AnnexA).Weidentifiedandencouragedinstitutionalresponsestoprovideuswithdataforeachoftheirinfrastructures.Thosefailinganycheckswerenotincludedintheanalysisforthisreport.ReasonsforexclusionarepresentedinChapter2,Figure2.1.

Duringdataexplorationfactualerrorswerecorrectedusinginformationprovidedinexplanatoryfieldsorthroughfurtherinvestigation,forexamplefollowingmisinterpretationofwhetherafundingsourcewaspublicorprivateorbycorrectingtypingerrors.Wealsoincludedtheoptionofaddingasupplementarysecondaryclassificationtoeachinfrastructure.Thisdidnotoverwritetheoriginaldatabutinsteadallowedadditionaldataexploration.

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AHRC ArtsandHumanitiesResearchCouncil

AI ArtificialIntelligence

AIRTO AssociationofInnovation,Research andTechnologyOrganisations

AMRC AdvancedManufacturing ResearchCentre

ATI AlanTuringInstitute

BAME Black,Asianandminorityethnicbackgrounds

BBSRC BiotechnologyandBiologicalSciencesResearchCouncil

BGS BritishGeologicalSurvey

BH&F Biologicalsciences,healthandfood

CCFE CulhamCentreforFusionEnergy

CCP5 ComputationalCollaborationProject No 5

CERN ConseilEuropéenpourlaRechercheNucléaire(EuropeanOrganisationforNuclearResearch)

CLF CentralLaserFacility

CLOSER Cohort&LongitudinalStudiesEnhancementResources

COAST Coastal,OceanAndSedimentTransport

Diamond DiamondLightSource

ECMWF EuropeanCentreforMedium-Range WeatherForecasts

E-INF Computationalande-infrastructure

ELIXIR Europeanlifescienceinfrastructureforbiologicalinformation

EMBL EuropeanMolecularBiologyLaboratory

EMBL-EBI EuropeanMolecularBiologyLaboratory-EuropeanBioinformaticsInstitute

ENV Environment

EPSRC EngineeringandPhysicalSciences ResearchCouncil

ESFRI EuropeanStrategyForumonResearchInfrastructures

ESO EuropeanSouthernObservatory

ESRC EconomicandSocialResearchCouncil

ESRF EuropeanSynchrotronRadiationFacility

ESS EuropeanSpallationSource

EU EuropeanUnion

EU-XFEL EuropeanX-rayFree-Electron LaserFacility

FAAM FacilityforAirborneAtmosphericMeasurements

FTE FullTimeEquivalent

G7 GroupofSeven(Canada,France,Germany,Italy,Japan,theUKand theUSA)

GLAM Galleries,Libraries,Archives andMuseums

HEI HigherEducationInstitute

HESA HigherEducationStatisticalAgency

HPC HighPerformanceComputing

ILL InstituteLaue-Langevin

IPERIONCH Europeanresearchinfrastructure forrestorationandconservationofCulturalHeritage.

ISIS ISISNeutronandMuonSource

JANET Ahigh-speednetworkfortheUK researchandeducationcommunity,providedbyJisc

JASMIN JointAnalysisSystemMeetingInfrastructureNeeds

JET JointEuropeanTorus

JWST JamesWebbSpaceTelescope

LHC LargeHadronCollider

LIGO LaserInterferometerGravitational-WaveObservatory

MAST MegaAmpSphericalTokamak

MC2 MaterialandChemical CharacterisationFacility

MRC MedicalResearchCouncil

N8 CollaborationoftheeightmostresearchintensiveuniversitiesinnorthernEngland

NERC NaturalEnvironmentResearchCouncil

NIAB NationalInstituteofAgriculturalBotany

NMR NuclearMagneticResonance

NNL NationalNuclearLaboratory

NNUF NationalNuclearUserFacility

ONS OfficeofNationalStatistics

ORE Offshorerenewableenergy

PS&E Physicalsciencesandengineering

PSRE PublicSectorResearchEstablishments

PV Photovoltaic

R&D Researchanddevelopment

SSAH Socialsciences,artsandhumanities

UCL UniversityCollegeLondon

UKDS UKDataService

UK-RIHS UKResearchInfrastructurefor HeritageScience

XML ExtensibleMarkupLanguage

Acronyms and Abbreviations

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Acronyms and Abbreviations References

1. DepartmentforBusiness,EnergyandIndustrialStrategy,TheUK’sIndustrialStrategy (websiteaccessedMay2019)

2. DepartmentforBusiness,Energy&IndustrialStrategy,InternationalComparativePerformanceoftheUKResearchBase,2019(websiteaccessedJuly2019)

3. InstituteforScientificInformation,TheAnnualG20Scorecard–ResearchPerformance2019 (websiteaccessedJuly2019)

4. EconomicInsight,WhatistheRelationshipbetweenPublicandPrivateInvestmentinScience,ResearchandInnovation?,2015(websiteaccessedJuly2019)

5. EstimatefromUKResearchandInnovationeconomicmodels(unpublished)

6. McKinseyGlobalInstitute,GlobalGrowth:CanProductivitySavetheDayinanAgingWorld?,2015

7. UKResearchandInnovation,InitialAnalysisofInfrastructureQuestionnaireResponsesandDescriptionoftheLandscape,2018

8. Independent,NumbersStudyingPhysicsRiseasBlockbusterFilms,theHadronColliderandtheMarsRoverInspireStudents,2015

9. EuropeanStrategyForumonResearchInfrastructuresScripta,Innovation-orientedCooperationofResearchInfrastructuresVol3,2018(websiteaccessedMay2019)

10. HMGovernment,InternationalResearchandInnovationStrategy,2019(websiteaccessedMay2019)

11. EuropeanCommission,AboutResearchInfrastructureswebpage(websiteaccessedJuly2019)

12. EuropeanSynchrotronRadiationFacility,ClearViewof“Robo”NeuronalReceptorOpensDoorforNewCancerDrugs(websiteaccessedApril2019)

13. DiamondLightSource,InsideDiamond,2017(websiteaccessedApril2019)

14. L’InstitutLaue-Langevin,NeutronsEnableFine-tuningofPesticidestoBoostCropYieldsandReduceEnvironmentalImpact(websiteaccessedApril2019)

15. EuropeanStrategyForumonResearchInfrastructures,TheESFRIMethodology (websiteaccessedMay2019)

16. G7Germany2015,GroupofSeniorOfficialsonGlobalResearchInfrastructuresProgressReport,2015(websiteaccessedMay2019)

17. HigherEducationStatisticsAgency,HigherEducationStaffData(websiteaccessedMay2019)

18. Technopolis,ScienceResearchInvestmentFund:AReviewofRound2andWiderBenefits,2009

19. ResearchEngland,ResearchandKnowledgeExchangeFundingfor2018-19:RecurrentGrantsandFormulaCapitalAllocations(2018)

20. OfficeforNationalStatistics,UKSIC,2007(websiteaccessedMay2019)

21. CreativeIndustriesClustersProgramme,BusinessofFashion,TextilesandTechnology(websiteaccessedMay2019)

22. NationalInstituteforHealthResearch,NIHRInfrastructure(websiteaccessedMay2019)

23. AdvancedManufacturingResearchCentre,Charities’FundingContributionstoUKMedicalResearchExcellence,2017(websiteaccessedMay2019)

24. EuropeanStrategyForumonResearchInfrastructures,Roadmap,2018(websiteMay2019)

25. Sci2(ScienceofScience)Tool,IndianaUniversityandSciTechStrategies,(websiteaccessedMay2019)

26. UKBiobank,Homepage(websiteaccessedMay2019)

27. MedicalResearchCouncil,ClinicalResearchCapabilitiesandTechnologiesInitiative(websiteaccessed May2019)

28. TheFrancisCrickInstitute,WorldwideInfluenzaCentre(websiteaccessedMay2019)

29. ThePirbrightInstitute,Homepage(websiteaccessedMay2019)

30. ScottishInformaticsandLinkageCollaboration,Homepage(websiteaccessedMay2019)

31. TheEuropeanBioinformaticsInstitute,Homepage(websiteaccessedMay2019)

32. EuropeanMolecularBiologyLaboratory,Homepage(websiteaccessedMay2019)

33. Data.parliament.ukWrittenEvidenceSubmittedbyCLOSER,2017(websiteaccessedMay2019)

34. HouseofCommons,Evidence-basedEarlyYearsIntervention:EleventhReportofSession2017–19,2018(websiteaccessedMay2019)

https://sci2.cns.iu.edu

114

35. HouseofCommons-ScienceandTechnologyCommittee,Evidence-basedEarlyYearsIntervention:Government’sResponsetotheCommittee’sEleventhReportofSession2017–19-FifteenthReportofSession2017–19,2019(websiteaccessedMay2019)

36. HistoricEngland,HeritageandtheEconomy2018,(websiteaccessedMay2019)

37. MetropolitanPolice,HateCrimeorSpecialCrimeDashboard(websiteaccessedMay2019)

38. DepartmentforBusiness,EnergyandIndustrialStrategy,CleanGrowthStrategy,2017 (websiteaccessedMay2019)

39. HMGovernment,TheUKLowCarbonTransitionPlan–NationalStrategyforClimateandEnergy,2009(websiteaccessedMay2019)

40. MissionInnovationSecretariat,MissionInnovation:AcceleratingtheCleanEnergyRevolution– Strategies,Progress,

PlansandFundingInformation,2017(websiteaccessedMay2019)

41. NASA,TechnologyReadinessLevels(websiteaccessedJune2019)

42. NewcastleUniversity,EnergySystemsIntegration(websiteaccessedMay2019)

43. HP-SIG,2017NationalE-infrastructureReport,2017(websiteaccessedMay2019)

44. EuropeanStrategyForumonResearchInfrastructures,ESFRIGlossary(websiteaccessedMay2019)

45. MappingoftheEuropeanResearchInfrastructureLandscape(MERIL),Homepage(websiteaccessed May2019)

the uk’s research and innovation infrastructure: landscape ......5 chapter 10: physical sciences...

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