Research Information Standards in Canada: From Specific Initiatives to Coordinated Efforts

1. Connecting Research • Research Information Standards in Canada: • From Specific Initiatives to Coordinated Efforts • Berlin, Germany • January 27th, 2014 • Yannick Machabée • Information analyst, Québec Research Funds (FRQ)

2. Agenda • My profile • Public research in Canada - Highlights • Key milestones in collecting Research Activity Data in Canada • Standards and Data Systems: Observations • Research classification: Context • Research classification: Qualities sought • Research classification: The 3-D taxonomy • Research classification: Examples • Conclusion

3. My profile • Background in civil engineering • Using research metrics since 15 years • FRQ information analyst for 10 years • Have developed reporting systems • Involved in common reporting and standardization initiatives in Canada for 10 years • Currently chairing CASRAI working group on research classification

4. Public research in Canada - Highlights • Canadian R&D: 50% publicly funded • (41% in Québec) • More than 75% of Canadian public research is done by universities • (more than 85% in Québec) • 98 universities in Canada (19 in Québec) • Québec universities: 9600 researchers • Québec university research funding: • 70% from Canadian public sources • Many sources of public funding at the federal and provincial levels

5. Key milestones in collectingResearch Activity Data in Canada • Some metrics are available from a long time: • Statistics Canada • - Nb of faculty members • - Nb of students • SIRU System of University Research Funding (Québec only) • - Standards for collecting data • - Centralized system / decentralized interfaces

6. Key milestones in collectingResearch Activity Data in Canada • Most of the other efforts were not part of a system • Groups like U15 and NAPHRO have worked and are still working on establishing or improving standards for research activities and impacts measurement • Public funders and some universities have built systems to collect information about research activities and research personnel

7. Key milestones in collectingResearch Activity Data in Canada 1997 • FRQ common CV (centralized interface) (Québec) • - Canadian Common CV (centralized interface) • └> Researchers Directory (Québec only) • - 3-D Research Classification(Québec) • - First version of CASRAI standards (Canada) • - New CCV (using CASRAI standards) • └> Canadian Researchers Directory (not online yet) • - CASRAI adopts 3-D Research Classification • - CASRAI developing standards for funding results and Health sector research impacts • - CASRAI improving 3-D Research Classification 2003 2011 2013-2014

8. Key milestones in collectingResearch Activity Data in Canada • CASRAI standards • Research Personnel Profile • Research Activity Profile (draft) • Research Impacts (under review) • 3-D Research Classification (under review)

9. Standards and Data Systems: Observations The best systems are fed by data owners e.g. a) publications by journals/authors b) funding by funders or fund managers c) research or transfer activities by researchers Problems come when: a) there is no reason for owners to provide the information b) owners are outside the scope of the system c) there are multiple owners on a single element => central management required?

10. Standards and Data Systems: Observations For metrics production, multiple owners are to be avoided / otherwise, a centralized body must manage codes or IDs Standards are necessary for compliance, but incentives are also required to get organizations to adopt it (3 levels): - Compliant products/softwares available (low) - Data sharing projects of interest (medium) - Obligation for owners to submit data (high) Legally, in Québec, owners or persons involved must give their consent to allow data sharing, except when the data are public

11. Standards and Data Systems: Observations Applying standards into interfaces raises issues that often require an update of the standards (applied validation phase needed) Within decentralized interfaces, standards are efficient only if: - Definitions are clear and accessible - Enough details on the elements of a standard are available to allow adopters to explain which information is expected - Understanding does not vary with translation

12. Research classification: Context • In 2002, Québec research authorities made two obser-vations regarding existing research classifications: • They were not able to answer the variety of needs emanating from: • Governments (accountability, justification of investments, identification of short, medium or long-term impacts, etc.) • Granting agencies and universities (strategic planning, presentation of clear information, etc.) • Organizations seeking a better focus on the response of university research to economic, technological, social or cultural problems • They did not properly reflect the current dynamics and complexity of university research

13. Research classification:Qualities sought • Simplicity, clarity and user-friendliness: must be easy for users to understand and employ (scientists, administrators, students, etc.) • Hierarchy: must comprise a reasonable number of classes divided into sub-classes so as to generate information according to several aggregation levels • Exhaustive and exclusive: must cover all research activities (i.e. natural sciences, engineering, health, humanities and social science, arts and letters); must present mutually exclusive dimensions

14. Research classification:Qualities sought • Operational: must enable quick and functional implementation, especially in terms of system and organizational capability • Adaptability and flexibility: must be able to factor in emerging themes as needed; must make it possible to characterize researchers and research projects separately; must take into account the new ways in which research is organized (increasingly multidisciplinary, cross-sectoral, inter-institutional, and even cross-community)

15. Research classification:Qualities sought • Continuity: must enable mapping tables to be developed for compatibility with main existing research classifications • Comparability: must be capable of being compared with other available Canadian and international classification systems, through the development of conversion tables

16. Research classification:The 3-D taxonomy Three-dimensional system that answers three basic questions about a researcher’s expertise or research work

17. Research classification:The 3-D taxonomy • Structure and logic: • Each dimension is independent of the others • Each dimension contains 2 or 3 hierarchical levels, with the possibility of fine or more aggregated analyses • The combination of the 3 dimensions allows characterization of the research activities of a researcher, a team or a centre from different points of view • Modeling of the 3 dimensions is based on the 4 main research sectors: - Natural Sciences and Engineering • - Health Sciences • - Human and Social Sciences • - Arts and literature

18. Research classification:Examples Researchers in Health sciences Researcher 1 Researcher 2 Researcher 3

19. Research classification:Examples Researchers in Health sciences Researcher 1 Researcher 2 Researcher 3

20. Research classification:Examples Researchers in Human and Social Sciences Researcher 1 Researcher 2 Researcher 3

21. Research classification:Examples Intersectoral case

22. Conclusion • I will be pleased to share thoughts an experiences with any of you • More information on CASRAI processes and standards are available on demand Thank you.