DATA MANAGEMENT PLANS & THE DATA CITATION INDEX

1. DATA MANAGEMENT PLANS & THE DATA CITATION INDEX NIGEL ROBINSON 19 MAY 2014

2. THE INCREASING VISIBILITY OF DATA “Data is the new gold” – NeellieKroes, EU Digital Agenda Commissioner • Grant funding agencies • Journal publishers • Publisher website • Electronic articles • Data repositories & registration agencies

3. DIGITAL SCHOLARSHIP

4. OVERVIEW Emerging landscape Opportunities Citation and attribution

5. THE EMERGENCE OF FUNDING MANDATES • NIH (2003) Data Sharing Policy that all funding applications of $500,000 or more per year are expected to address data-sharing in their application. • NSF (2011) All funding proposals submitted on or after January 18, 2011, must include a “Data Management Plan” describing how the proposal will conform to NSF policy on the dissemination and sharing of research results.

6. DATA MANAGEMENT REQUIREMENTS EXTEND ACROSS THE GLOBE Aug 2011… “expectation that all our funded researchers should maximise access to their research data with as few restrictions as possible. …. submit a data management and sharing plan as part of the application process.” 2007… “Researchers are to retain research dataand primary materials, manage storage of research data and primary materials, maintain confidentiality of research data and primary materials.”

7. DATA MANAGEMENT REQUIREMENTS EXTEND ACROSS THE GLOBE “A further new element in Horizon 2020 is the use of Data Management Plans (DMPs) detailing what data the project will generate, whether and how it will be exploited or made accessible for verification and re-use, and how it will be curated and preserved. The use of a Data Management Plan is required for projects participating in the Open Research Data Pilot. Other projects are invited to submit a Data Management Plan if relevant for their planned research.”

8. IMPACT ON RESEARCH LIBRARIES 8

9. FUNDING MANDATES BECOMING STRONGER • January 14, 2013… “failure to provide the requisite Data Management Plan will result in the application being rejected or terminated.”

10. WHY SHARE DATA? Data sharing leads to more science & more knowledge Verification - Findings can be verified Extend original findings, address new questions Reduce costs Training – data reuse Increased primary publicationsA. Pienta, G. Alter, J. Lyle (2010). The Enduring Value of Social Science Research: The Use and Reuse of Primary Research Data. http://hdl.handle.net/2027.42/78307

11. DATA SHARING 25% share before and after publication The level and timing of data sharing varies

12. INCREASED CITATION WITH SHARED DATA Bibliometrics 35% to 69% more citations Piwowar HA, Day RS, Fridsma DB (2007) Sharing Detailed Research Data Is Associated with Increased Citation Rate. PLoS ONE 2(3): e308. doi:10.1371/journal.pone.0000308 courtesy of Jon Sears (AGU)

13. DEPOSITION OF DATA BY RESEARCHERS 13

14. RESEARCHERS NOT RECEIVING CREDIT • Barriers to creating and sharing data: • Researchers are hesitant to spend time and effort to create and share data because they don’t feel the work is adequately exposed or accredited • Researchers find it difficult to expose data they have produced because datarepositories do not have clear standards or mechanisms in place for doing so 14

15. RESEARCHER PROBLEMS Access & discovery Citation standards Lack of willingness to deposit and cite Lack of recognition / credit

16. DATA MANAGEMENT PLAN BENEFITS

17. CHALLENGES • Metadata • Resources • Expertise • Citable data source • Metadata quality • Unique & persistent identifiers • Consistency • Data repositories are not static • How is version control handled? • Partnerships

18. DATA CITATION Current citation style (in full text of article as informal citations) Desired/future citation style (as formally cited references) U.S. Dept. of Justice, Bureau of Justice Statistics (1996): MURDER CASES IN 33 LARGE URBAN COUNTIES IN THE UNITED STATES, 1988. Version 1. Inter-university Consortium for Political and Social Research. http://dx.doi.org/10.3886/ICPSR09907.v1 Lee, Seung-Jae; Lee, He-Jin; Cho, Ji-Hoon; Rho, Sangchul; Hwang, Daehee (2008): GSE11574: The responses of astrocytes stimulated by extracellular a-synuclein. Gene Expression Omnibus. http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE11574

19. DATA CITATION Lee, Seung-Jae; Lee, He-Jin; Cho, Ji-Hoon; Rho, Sangchul; Hwang, Daehee (2008): GSE11574: The responses of astrocytes stimulated by extracellular a-synuclein. Gene Expression Omnibus. http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE11574 Published data sets Data Citation Index New data metrics Scientific literature

20. DATA CITATION INDEX AIMS • Launched October 2012 4M data records Enable the discovery of data repositories, data studies and data sets in the context of traditional literature Link data to research publications Help researchers find data sets and studies and track the full impact of their research output Provide expanded measurement of researcher and institutional research output and assessment Facilitate more accurate and comprehensive bibliometric analyses

21. INDEXING A DATA REPOSITORY ON WEB OF SCIENCE Record Types • Repository/Source: Comprises data studies, data sets and/or microcitations. Stores and provides access to the raw data. • DataStudy: Descriptions of studies or experiments with associated data which have been used in the data study. Includes serial or longitudinal studies over time. • Data Set: A single or coherent set of data or a data file provided by the repository, as part of a collection, data study or experiment. • Microcitation: (nanopublication) An assertion about concepts that have been found to be linked by scientific enquiry, and can be uniquely identified and attributed to its author. Made up of three separate parts: a subject, a predicate and an object.

22. Search Results within the Data Citation Index present the powerful Web of Knowledge options for exploring a body of information. Data becomes discoverable alongside literature

23. Data deposition makes it possible to show related data from the repository

24. Because data are accessible and able to be cited, they can be linked to publications describing research which uses them

25. Link out directly to the original item, in this case a Data Study.

26. Start to build citation maps associated with data through the association of data and literature

27. Provide assistance in how to associate data and literature through citation

28. DATA CITATION INDEX & DATA MANAGEMENT PLANS Discovery of data most important to scholarly research Data linked to published research literature Measures of data citation, use and reuse with attribution assisted by identifiers New metrics for digital scholarship

29. Thank you Nigel Robinson nigel.robinson@thomsonreuters.com

30. REPOSITORY SELECTION & EVALUATION • As we evaluate repositories for inclusion, some of the things we consider are: • Editorial Content - ensuring that material is desirable to the research community. • Persistence and stability of the repository, with a steady flow of new information. • Thoroughness and detail of descriptive information. • Links from data to research literature.

31. DATA REPOSITORIES Over 1000 repositories identified

32. TYPES OF DATA BY DISCIPLINE