©keith g jeffery/ anne assersonsupporting the research process with a cris cris2006 1 supporting...
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©Keith G Jeffery/Anne Asserson Supporting the Research Process with a CRIS
CRIS2006 1
Supporting the Research Process
with a CRISKeith G Jeffery Director IT CLRC [email protected] President, euroCRIS
Anne Asserson Senior ExecutiveOfficer [email protected] University of Bergen
©Keith G Jeffery/Anne Asserson Supporting the Research Process with a CRIS
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Agenda
• The Issue• The Proposition• The Research Process• Dealing With the Issue• The Metadata• Conclusion
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The Issue
• Increasing numbers of researchers• Increasing output per researcher
– Publications– Patents– Products
• Especially research datasets from automated equipment
• Effort to catalog - input metadata– Too great (for the user)– Does not scale (with increasing numbers)
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Agenda
• The Issue• The Proposition• The Research Process• Dealing With the Issue• The Metadata• Conclusion
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The Proposition
• The research process provides the context– Link the CERIF-CRIS information to the research
output information• Provides context• Provides some of the required metadata
– Collect metadata fragments • Only once• As early as possible (as they are generated)
• Result– Research output
• Publications, patents, products– Linked together in context by the CERIF-CRIS
• Person, Project, OrgUnit, Funding, Event, Facility, Equipment
– With provenance and curation managed automatically
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The Notion
• The research process is a workflow with e-forms– At each step (meta) information is required
and stored incrementally (re-use, minimal effort)
• The researcher sees benefit from the process: examples– Automated CV– Automated publication list– Tracking competing and cooperating teams– Research visible to intermediaries for
exploitation– Boilerplate information for research proposals
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Agenda
• The Issue• The Proposition• The Research Process• Dealing With the Issue• The Metadata• Conclusion
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The R&D Process: Recording
Workprogramme
Proposal
Project
Results
Exploitation
WealthCreation
CRISDATABASE
Information from external systems and CRIS
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The R&D ProcessRecording WorkProgramme
Workprogramme ProgrammeNameFundingOrgUnitPerson
Workprogramme document
CRISDATABASE
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The R&D ProcessRecording Proposal
Proposal
TitleAbstract
Person(s)OrgUnit(s)
Proposal Document
CRISDATABASE
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The R&D ProcessRecording Project
Project
TitleAbstract
Person(s)OrgUnit(s)
FundingProject Plan
CRISDATABASE
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The R&D ProcessRecording Results-Product
Results
Person(s)OrgUnit(s)Project(s)
Product(s)Product Description
CRISDATABASE
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The R&D ProcessRecording Results-Patent
Results
Person(s)OrgUnit(s)Project(s)Patent(s)
Patent File
CRISDATABASE
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The R&D ProcessRecording Results-Publication
Results
Person(s)OrgUnit(s)Project(s)
Bibliographic InformationArticle
CRISDATABASE
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The R&D ProcessRecording Exploitation
Exploitation
Person(s)OrgUnit(s)
Business planFinance Data
Marketing DataProduction Data
Sales Data
CRISDATABASE
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The R&D ProcessRecording Wealth Creation
WealthCreation
Person(s)OrgUnit(s)
Annual Reports/AccountsEmployment Records
Dividends Records
CRISDATABASE
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The R&D Process
Workprogramme
Proposal
Project
Results
Exploitation
WealthCreation
Note:
some CRIS developers limit recording of outputs from the process to areas indicated
Nirvana
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CRIS Features Required
• Entity instance attribute data collected once and stored
• Entity instances related flexibly (n:m)• Entity instances related by role and temporal
limits (semantics)• Input incremental, flexible, validated (minimum
effort)• System extensible (add new attributes,entities
preserving previous datastructure for interoperation)
• System interoperable – CRIS (to create world view)
• System linkable – other systems used in research process (eg finance, HR, project management to utilise them for CRIS purposes)
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CERIF-CRIS
• It is no accident that CERIF (Common European Research Information Format) provides a datamodel with exactly these desirable properties.
• Linking relations are the key feature – temporal and role information
• Critical to answer questions like:– “during what time interval was person A
project leader of project P?” – “to which research group(s) did person A
belong when she produced publication X?”
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CERIF-CRISFurther features
• Inference: – in a multidimensional framework, – deduction or induction of relationships between
entities• eg between a grey internal report and a white published
paper - and with other research outputs such as datasets or software.
• Fact generation– automated generation of facts
• eg (1) Person A on Project P produces Paper X;• (2) Project P uses Equipment E• Person A uses Equipment E
– the generated data may be • recorded in the CERIF-CRIS • deduced / induced afresh each time it is required.
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CERIF-CRISFurther features
• Assertions– relationships between entity instances (eg documents)
can also be expressed explicitly (i.e. asserted)• eg references and / or citations can be recorded by
directly inputting the information into the CERIF-CRIS.
• Metrics– role-based temporal relationships between entity
instances (eg publications)– provides detailed research output metrics, – increasingly in demand from CRISs as research
institutions seek to justify their funding and to improve their relative standing in league tables
– while funding organisations seek to justify their decisions.
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CERIF-CRISSummary
• through the flexible and dynamic linking relations between entities, – with their role and time-stamped attributes,
• a rich context for understanding the R&D output is provided, including versions, history and provenance.
• This context is particularly important for other users of CRISs such as – entrepreneurs engaged in technology transfer and
wealth creation – the media explaining to the public the importance of
the research being done.
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CERIF-CRIS at the Centre
• Acting as metadata• Relating CRIS information to itself
– Flexible linking relations
• And to information in other systems– Eg publications repository– Eg e-research datasets and software
• And Via GRIDs environment to other research process systems– E.g. finance, HR, project management
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CERIF-CRIS at the Centre
Portal with knowledge-assisted user interface
Digital Curation Facility
SCIENTIFIC DATASETS
Data
Information
Knowledge
PUBLICATIONS
Data
Information
Knowledge metadata
publish
validate
GRIDs
Ambient, Pervasive Access
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Agenda
• The Issue• The Proposition• The Research Process• Dealing With the Issue• The Metadata• Conclusion
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Dealing with the Issue: Progressive
Recording• early research ideas or work in
progress : grey document – described by appropriate metadata
(title, abstract….) input at the time of deposit.
– publication metadata linked to pre-existing research information (such as person, organisational unit, project) in a temporal and role-based context.
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Progressive Recording
Grey DocumentGreydoc
Publicationmetadata
Person
Project
OrgUnit
new
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Dealing with the Issue: Progressive
Recording• early research ideas or work in progress :
grey document – described by appropriate metadata (title,
abstract….) input at the time of deposit. – publication metadata linked to pre-existing research
information (such as person, organisational unit, project) in a temporal and role-based context.
• grey document developed into a white publication– additional publication metadata is input at the time
of submission. – linked through temporal and role-based
relationships to the pre-existing grey publication – and to the pre-existing contextual information such
as persons, organisational units etc.
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Progressive Recording
White documentGreydoc
Publicationmetadata
Person
Project
OrgUnit
Whitedoc
Publicationmetadata
new
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Dealing with the Issue: Re-Use for
Scalability• Record (meta)data once: re-use
many times• Record only the metadata available
and needed at each process step– Automated input assistance - quality– Reduces input required
• Addresses scalability and high user effort threshold, improves quality
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Agenda
• The Issue• The Proposition• The Research Process• Dealing With the Issue• The Metadata• Conclusion
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MetadataWhere to Store it
• In the repository (publications or e-research datasets, software)
• In the CERIF-CRIS
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Metadata in the Repository
• Advantages– Metadata with the object
• Available for retrieval, statistical processing, advanced computation…
• Available for harvesting (eg OAI-PMH)
• Disadvantages– Metadata not available in CERIF-CRIS for
management information– Most repositories only store poor metadata
• non-machine-understandable• Insufficient for bibliographic reference• No DOI to link to publisher database
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Metadata in the CERIF-CRIS
• Advantages– Efficient processing of management
information queries • Disadvantages
– Have to somehow redirect OAI-PMH harvesting to CERIF-CRIS instead of repository
– Separate metadata from the full hypermedia article, research dataset or software
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The Solution: Metadata in CERIF-CRIS and
Repository• Primary metadata source is in the
CERIF-CRIS– Linked with research process workflow– Incremented as generated– Provenance and context– Validation – quality– Generate bibliographic references
• Copy in the repository– For harvesting (articles)– With additional detailed metadata for
research datasets or software
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The Solution: Metadata in CERIF-CRIS and
Repository• Discussion
– Parts of (meta)data stored twice, but • storage is cheap• Research process workflow means only input
once
– Improved quality through validation due to context and provenance
– Management Information processing performed in one system and separated from access to the research articles, datasets or software
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Agenda
• The Issue• The Proposition• The Research Process• Dealing With the Issue• The Metadata• Conclusion
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Conclusion
• The solution presented works in prototype designs:– UiB: FRIDA (CERIF-CRIS) linked to
DSpace– CCLRC: CDR (CERIF-CRIS) linked to
ePubs (articles) and e-Research portal (datasets and software)
• And is now being implemented in production