1. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 1 Supporting the Research Process with a CRIS Keith G Jeffery Director IT CLRC k.g.jeffery@rl.ac.uk President, euroCRIS Anne Asserson Senior ExecutiveOfficer anne.asserson@fa.uib.no University of Bergen

2. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 2 Agenda The Issue The Proposition The Research Process Dealing With the Issue The Metadata Conclusion

3. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 3 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)

4. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 4 Agenda The Issue The Proposition The Research Process Dealing With the Issue The Metadata Conclusion

5. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 5 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

6. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 6 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

7. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 7 Agenda The Issue The Proposition The Research Process Dealing With the Issue The Metadata Conclusion

8. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 8 The R&D Process: Recording Workprogramme Proposal Project Results Exploitation WealthCreation CRIS DATABASE Information from external systems and CRIS

9. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 9 The R&D Process Recording WorkProgramme Workprogramme ProgrammeName Funding OrgUnit Person Workprogramme document CRIS DATABASE

10. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 10 The R&D Process Recording Proposal Proposal Title Abstract Person(s) OrgUnit(s) Proposal Document CRIS DATABASE

11. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 11 The R&D Process Recording Project Project Title Abstract Person(s) OrgUnit(s) Funding Project Plan CRIS DATABASE

12. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 12 The R&D Process Recording Results-Product Results Person(s) OrgUnit(s) Project(s) Product(s) Product Description CRIS DATABASE

13. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 13 The R&D Process Recording Results-Patent Results Person(s) OrgUnit(s) Project(s) Patent(s) Patent File CRIS DATABASE

14. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 14 The R&D Process Recording Results-Publication Results Person(s) OrgUnit(s) Project(s) Bibliographic Information Article CRIS DATABASE

15. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 15 The R&D Process Recording Exploitation Exploitation Person(s) OrgUnit(s) Business plan Finance Data Marketing Data Production Data Sales Data CRIS DATABASE

16. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 16 The R&D Process Recording Wealth Creation WealthCreation Person(s) OrgUnit(s) Annual Reports/Accounts Employment Records Dividends Records CRIS DATABASE

17. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 17 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

18. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 18 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)

19. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 19 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?”

20. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 20 CERIF-CRIS Further 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.

21. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 21 CERIF-CRIS Further 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.

22. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 22 CERIF-CRIS Summary 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.

23. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 23 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

24. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 24 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

25. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 25 Agenda The Issue The Proposition The Research Process Dealing With the Issue The Metadata Conclusion

26. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 26 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.

27. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 27 Progressive Recording Grey Document Grey doc Publication metadata Person Project OrgUnit new

28. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 28 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.

29. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 29 Progressive Recording White document Grey doc Publication metadata Person Project OrgUnit White doc Publication metadata new

30. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 30 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

31. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 31 Agenda The Issue The Proposition The Research Process Dealing With the Issue The Metadata Conclusion

32. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 32 Metadata Where to Store it In the repository (publications or e-research datasets, software) In the CERIF-CRIS

33. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 33 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

34. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 34 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

35. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 35 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

36. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 36 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

37. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 37 Agenda The Issue The Proposition The Research Process Dealing With the Issue The Metadata Conclusion

38. ©Keith G Jeffery/ Anne AssersonSupporting the Research Process with a CRIS CRIS2006 38 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