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  • LIBER:Collaborate to Share

    RDA Florence, 14 November, 2016Susan Reilly, Executive Director, LIBER

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  • Overview

    Open data in the LIBER visionBenefits of open dataFAIR dataSupporting FAIR Data

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  • LIBER is Europes largest research library network

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  • MissionEnable world class research= CollaborativeGrowth in collaboration from 13% (2003)- 17% (2011)

    = International40% of French & German research outputs a result of international collaborationRate of citation grows as geographic extent of collaboration increases

    =InterdisciplinaryFoundation of frontiers research

    =Data intensivesupports interdisciplinary exploration

    and open

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  • 2022Libraries powering sustainable knowledge in the digital ageVision

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  • VisionOpen Access is the defaultResearch data is FAIRDigital skills underpin open, transparent research lifecycle Research infra is participatory and tailored to different disciplinesCutural heritage build on todays digital info2022

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  • Knowledge as a Public GoodNon rivalrous-sharing it doesnt deplete it as a resourceNon excludable-its impossible stop the supply of knowledgeCopyright reconises this by only exerting control over the expression of an idea not the idea itselfIn the digital age data can be infinately accessible

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  • Benefits of Open Data

    For societySolves global challenges e.g. hunger, pollutionFor researchers:Data re-use, avoiding costly duplicationData re-use,facilitate complex interdisciplinary enquiryValidation of results quality controlFor policy: Inform decision makingFor industry:In development of new products & services

    Humanitarian Data Exchange*

  • Fake data!

    Chris Hargerink developing software to detect signs of data fabrication*

  • BarriersCultural differencesDefinition of research dataLack of skills/educationPoorly defined roles and responsibilitiesLack of infrastructureLack of career incentives

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  • European Member States CommitmentAll member states to transition towards Open Science (council conclusion May 2016)Open access the default by 2020Research data from publically funded projects a public goodData management standard scientific practiceDMPs obilgatory Follow FAIR principles

    AGREES that the results of publicly funded research should be made available in an as open as possible manner and ACKNOWLEDGES that unnecessary legal, organisational and financial barriers to access results of publicly funded research should be removed as much as possible and appropriate in order to attain optimal knowledge sharing, taking into account when necessary the need for exploitation of results; ENCOURAGES the Commission and Member States to further engage with third countries in order to accelerate the transition process to open science and to ensure mutual benefits regarding open access to scientific publications and optimal reuse of research data in a global context. as open as possible, as closed as necessary. *

  • EU Horizon 2020 MandatesOpen Access Mandatory (2015)Open Data Pilot (7 funding areas, 2015)Open Data pilot extended to all funding areas from 2017

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  • H2020 Open Data PilotOpt out at any stage (1/3 opted out so far)All research data, including metadata, needed to validate the results in a peer-reviewed publicationOther curated or raw data, and its associated metadata, specified in the DMP even if it did not result in a publicationDocumentation, software, hardware or tools required to enable reuse of the dataDMP obilgatory

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  • http://knowledgebase.e-irg.eu/documents/243153/246094/E-infrastructures+-+making+Europe+the+best+place+for+research+and+innovation.pdf

  • The European Open Science CloudA virtual environment to store and process large volumes of information http://libereurope.eu/blog/2015/11/04/an-open-and-community-driven-open-science-cloud

    EOSC as the EU contribution to a future, global Internet of FAIR Data and Services underpinned by open protocols.*

  • The Challenge

    Research data are the evidence that underpins the answer to the research question, and can be used to validate findings regardless of its form

    These might be quantitative information or qualitative statements collected by researchers in the course of their work by experimentation, observation, modelling, interview or other methods, or information derived from existing evidence. Data may be raw or primary (e.g. direct from measurement or collection) or derived from primary data for subsequent analysis or interpretation (e.g. cleaned up or as an extract from a larger data set), or derived from existing sources where the rights may be held by others. Data may be defined as relational or functional components of research, thus signalling that their identification and value lies in whether and how researchers use them as evidence for claims.*

  • Research Data is

    ODE data publication pyramid

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  • Research Data isFindableMetadataPersistent identifiersIndexed in a searchable resourceAccessible (openly)Open and standardised communication protocolsInteroperableShared language for knowledge representationReusableClear provenance and licencesDetailed provenance

    applied to both human-driven and machine-driven activities, its a big job!*

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  • Supporting FAIR DataActiveOffering and planning RDS serviceConsultative (Discussion e.g. metadata, policy, training, outreach)38% provide tech supportOn the horizon 42% plannig tech support48% planning ID support43% planning metadata servicesWest and north more involved in discussions

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  • FindableData management planning support (46%)IdentifiersSupport for citation and finding datasetsIdentification of datasets for repositories

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  • AccessibleConsulting on data standards and methodsPreparing datasets for deposit 25%Web guidesData storage 78%

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  • InteroperableConsulting on data standards and methods (44%)Partnering with researchers (32%)ID DatasetsCollaborating with disciplinary departmentsCollaborting with other institutions and infra

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  • ReusablePolicy development and planning (66%)Gudiance and training e.g. re copyright (54%)Tools for data analysis (23%)

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  • Research Data Services in LibrariesConsultativeConsultativeConsultativeConsultativeConsultativeConsultative

    Chart1

    0.43

    0.44

    0.46

    0.54

    0.66

    0.77

    Consultative RDS LIBER

    Discussing RDS with others (n=93)Up to 9,99976.2%

    10K-24,99975.7%

    25,000+82.9%

    Involved in policy development related to RDS (n=92)Up to 9,99970%

    10K-24,99962.2%

    25,000+68.6%

    Training colleagues on RDS (n=93)Up to 9,99947.6%

    10K-24,99940.5%

    25,000+74.3%

    Consulting with academic staff or students on DMPs (n=105)Up to 9,99936%

    10K-24,99943.2%

    25,000+55.6%

    Consulting with academic staff or students on meta/data stds (n=103)Up to 9,99939.1%

    10K-24,99940.9%

    25,000+50.0%

    Consultative RDS LIBER

    Yes Only Responses

    Q14 ranked

    Other (n=2)2%

    Collaboration with others with skills related to RDS (n=8)7%

    In-house staff workshops (n=41)35%

    Support for staff to join working groups related to RDS (n=51)43%

    Support for staff to take courses related to RDS (n=52)44%

    Support for staff to attend conferences/workshops (n=68)57%

    Q14 ranked

    RDS offered by response rate

    Outreach/collaboration with other RDS providers43%

    Consulting on data and metadata standards44%

    Consulting on data mgt plans46%

    Training colleagues on RDS54%

    Involved in policy development/planning66%

    Discussing RDS with others77%

    RDS offered by response rate

    *yes only responses*Outreach/collaboration with other RDS providers (n=107) Consulting on data and metadata standards (n=105) Consulting on data mgt plans (n=107) Training colleagues on RDS (n=95) Involved in policy development/planning (n=95) Discussing RDS with others (n=95) *

  • ConsultativeConsultativeConsultativeTechnicalTechnical

    Chart1

    0.26

    0.32

    0.35

    0.37

    0.38

    Consultative RDS LIBER

    Discussing RDS with others (n=93)Up to 9,99976.2%

    10K-24,99975.7%

    25,000+82.9%

    Involved in policy development related to RDS (n=92)Up to 9,99970%

    10K-24,99962.2%

    25,000+68.6%

    Training colleagues on RDS (n=93)Up to 9,99947.6%

    10K-24,99940.5%

    25,000+74.3%

    Consulting with academic staff or students on DMPs (n=105)Up to 9,99936%

    10K-24,99943.2%

    25,000+55.6%

    Consulting with academic staff or students on meta/data stds (n=103)Up to 9,99939.1%

    10K-24,99940.9%

    25,000+50.0%

    Consultative RDS LIBER

    Yes Only Responses

    Q14 ranked

    Other (n=2)2%

    Collaboration with others with skills related to RDS (n=8)7%

    In-house staff workshops (n=41)35%

    Support for staff to join working groups related to RDS (n=51)43%

    Support for staff to take courses related to RDS (n=52)44%

    Support for staff to attend conferences/workshops (n=68)57%

    Q14 ranked

    RDS offered by response rate

    Outreach/collaboration with other RDS providers (n=107)43%

    Consulting on data and metadata standards (n=105)44%

    Consulting on data mgt plans (n=107)46%

    Training colleagues on RDS (n=95)54%

    Involved in policy development/planning (n=95)66%

    Discussing RDS with others (n=95)77%

    ID datasets26%

    Direct participation with researchers32%

    Creating webguides35%

    Providing ref. support for finding/citing data37%

    Providing tech. support for