1. Opportunities and Challenges: Implementing Data Citation Standards Jeri Schneider, ICPSR IASSIST 2006 Conference Ann Arbor, MI May 26, 2006

2. Overview  ICPSR’s Bibliography of Data- Related Literature— accomplishments, obstacles  Future citation landscape  How do we get there from here?  Unresolved issues

3. ICPSR’s Bibliography of Data-Related Literature  39,000+ citations to over 4,000 studies  2,000+ journals, 23,000+ journal articles  Access bibliography for study: Search for study  Select “Related Literature” tab at top of study description http://www.icpsr.umich.edu/access/index.h tml

4. Current Citation Landscape

5. Future Citation Landscape  Data Citation Index—”Association of Ideas”  Data Mining http://www.touchgraph.com  Subject searches, associations  How do we get there from here?here

7. Establish Official Standard (e.g. ISO) Develop Culture of Citing DataDevelop Technology Infrastructure Develop New Tools Based on Data Citations Dynamic Links from e-Publications to Data Automated Data Citations Index/Bibliographies Graphical Web of Data/Publications Associations Develop Citation Standard/Guidelines (IASSIST) Unresolved Issues

8. Step 1: Develop Citation Standard/Guidelines (IASSIST)  Agree on necessary citation elements  Develop and publish recommendation

9. Establish Official Standard  ISO, etc.

10. Develop Culture of Citing Data  P.I.s—archive/distribute data, titles  Authors—proper citation (when, how, where to cite)  Publishers/Editors—enforce  Citation manuals—APA, MLA, Chicago  Libraries  WHO ELSE???  Ego factor  Practice of citing data will grow exponentially as benefits are realized

11. Develop Technology Infrastructure  Archives—unique identifiers/keys, versions  Citation software—EndNote, ProCite, etc.  Publishers & editors—develop/adopt their own formats based on standard  Digital content providers—develop links, integrate with current products, create new products (web/association of ideas)  OTHERS?

12. Automated Data Citations Index/Bibliographies  Machine-readable citations will enable the development of mechanisms to automatically collect citations into an index, for rapid creation of study bibliographies and other associated lists

13. Unresolved Issues  What constitutes “data use” that warrants citation? What constitutes “data use” that warrants citation?  What if there are multiple versions of data available, and/or same data from multiple sources? What if there are multiple versions of data available, and/or same data from multiple sources?  How do we identify data citation as “data”? How do we identify data citation as “data”?  WHAT ELSE??? WHAT ELSE???

14. What constitutes “data use”?  Data are central to argument  Data are used to generate one table (or 20 tables?)  Data are used as comparison to central data used  Data collection/methodology are described or critiqued  What else???

15. Multiple versions, multiple sources?  Can we design citations and/or technology infrastructure so that users can effectively perform multiple tasks: Link to original data used, from original source (or from alternate source) AND Link to the same studies from multiple sources AND Link to various versions of data from same study

16. How to identify data citation as “data”?  Can we agree on terminology, or set of terms, that both users and machines will understand?

17. Interested Parties  Principal investigators Release/archive data Title Versions  Archives Release Versions Standard number/key identifier  Authors—when, how, where to cite?  Publishers/Editors—print and digital—enforcers?  Electronic content providers—links, enforcers? Integrate with current products, create new products (web/association of ideas)  Citation software developers—EndNote, ProCite, RefWorks, etc.  Who else???

18. Next Steps  Share citation guidelines—find commonalities, differences  Hold meeting to resolve differences  Publish IASSIST guide  Divide tasks—make contacts, publish, present (develop culture, infrastructure)

19. See also:  Dodd, Sue. (1979) “Bibliographic references for numeric social science data files: Suggested guidelines.” Journal of the American Society for Information Science, 30 (2), 77-82.  Dodd, Sue. (1990) “Bibliographic References for Computer Files in the Social Science: A Discussion Paper.” Chapel Hill, NC: Institute for Research in Social Science, University of North Carolina. http://www.people.virginia.edu/~pm9k/info/compRef.html  Schneider, Jeri. (2006) “Why we need a data citation standard: Lessons learned from compiling ICPSR’s Bibliography of Data- Related Literature.” ICPSR Bulletin, 26 (2), 9-12. http://www.icpsr.umich.edu/org/publications/bulletin/spr06.pdf  Contact: Jeri Schneider, ICPSR - jeris@umich.edu