2013 DataCite Summer Meeting - Thomson Reuters Data citation index cooperation (Nigel Robinson - Thomson Reuters)

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2013 DataCite Summer Meeting - Making Research better …

2013 DataCite Summer Meeting - Making Research better

DataCite. Co-sponsored by CODATA.

Thursday, 19 September 2013 at 13:00 - Friday, 20 September 2013 at 12:30

Washington, DC. National Academy of Sciences

http://datacite.eventbrite.co.uk/

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  • 1. DISCOVERY, ACCESS, AND CITATION OF PUBLISHED RESEARCH DATA NIGEL ROBINSON 20 SEPTEMBER 2013 THE DATA CITATION INDEX - PARTNERSHIP WITH DATACITE
  • 2. ©2010ThomsonReuters OVERVIEW • What is the Data Citation Index? • Building the Data Citation Index • Challenges • Partnership with DataCite
  • 3. ©2010ThomsonReuters DEPOSITION OF DATA BY RESEARCHERS 3 24% 36% 47% 51% 17% Publisher website Repository managed by a third party (e.g, domain-… Department or institutional repository Personal website Other Q16. Where do you place your non-traditional scholarly output to make it available to others? (n=471)
  • 4. ©2010ThomsonReuters RESEARCHERS NOT RECEIVING CREDIT 4 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 are finding it difficult to expose data they have produced because data repositories do not have clear standards or mechanisms in place for doing so
  • 5. ©2010ThomsonReuters BARRIERS TO RESEARCHERS CITING DATA Researchers agree that data should be cited, but there are currently no universally accepted standards for citing data 5 “Lack of knowledge about standards for citation and of proper scholarly recognition and/or evaluation of such materials.”… “…cumbersome citation formats including very long internet addresses.” “Incomplete citation information available (dates and real author names as distinct from aliases)’”
  • 6. ©2010ThomsonReuters BENEFITS OF RESEARCH DATA SHARING • Advancement of scholarship • Verification of results • Promotion of scholar’s work
  • 7. ©2010ThomsonReuters RESEARCHER PROBLEMS • Access & discovery • Citation standards • Lack of willingness to deposit and cite • Lack of recognition / credit
  • 8. ©2010ThomsonReuters IMPACT ON RESEARCH LIBRARIES 8
  • 9. ©2010ThomsonReuters DATA CITATION INDEX AIMS Launched October 2012 3M 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
  • 10. ©2010ThomsonReuters 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. REPOSITORY SELECTION & EVALUATION
  • 11. ©2010ThomsonReuters REPOSITORY EVALUATION • Repository must hold data • Repository must provide access to dataData deposit • Material added/updated • Provide statistics on deposited data • Actively curate data in the archive Active • Persistent IDs, DOIs or other permanent ID • Contacts available for confirmation of interpretation • Indication of intention to preserve data or provide access over the long term • Contingency if repository was to cease to operate • Make data accessible (or state licensing terms) • Sustainable • Funding information available for repository and deposited data Persistent • Links to literature • Citation in literature databasesProof of reuse
  • 12. ©2010ThomsonReuters DATA REPOSITORIES • Over 850 repositories identified
  • 13. ©2010ThomsonReuters TYPES OF DATA BY DISCIPLINE ART & HUMANITIES CULTURAL HERITAGE LANGUAGE CORPUS IMAGE COLLECTIONS RECORDINGS SOCIAL SCIENCES POLL DATA ECONOMIC STATISTICS LONGITUDINAL DATA NATIONAL CENSUS PUBLIC OPINION SURVEYS SCIENCE & TECHNOLOGY MAPS ALGORITHMS GENOMICS SKY SURVEYS ASTROPHYSICS REMOTE SENSING MUSEUM SPECIMENS
  • 14. ©2010ThomsonReuters INDEXING A DATA REPOSITORY ON WEB OF KNOWLEDGE • Repository/Source: Comprises data studies, data sets and/or microcitations. Stores and provides access to the raw data. • Data Study: 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. 14 Record Types Descriptive metadata feed from repository Repository raw metadata is analysed Metadata added Repository Data study Data set Micro- citation
  • 15. ©2010ThomsonReuters Search Results within the Data Citation Index present the powerful Web of Knowledge options for exploring a body of information.
  • 16. ©2010ThomsonReuters Link to all Data Citation Index content associated with this particular Repository.
  • 17. ©2010ThomsonReuters Link out directly to the original item, in this case a Data Study.
  • 18. ©2010ThomsonReuters REQUIREMENTS & CHALLENGES • Metadata availability – Lack of repository resources – Lack of repository expertise • Citable data source • Metadata quality – Clean & consistent metadata – Metadata inconsistencies – Consistent file format • Desirable characteristics – English language for key metadata fields – Metadata curation and quality control – Required metadata fields present for citation – Data dictionary and schema available – Consistent metadata to allow mapping to DCI fields – Member of extended network • Data repositories are not static • Partnerships
  • 19. ©2010ThomsonReuters Data Citation Index Repository 1 Repository 2 Repository 3 DATA CITATION INDEX - METADATA PARTNERSHIPS DataCite Repository 1 Repository 2 Repository 3 Data Citation Index DataCite
  • 20. ©2010ThomsonReuters DATACITE PARTNERSHIP • Repositories providing enhanced metadata to DataCite are included in the Data Citation Index – Expanded data visibility through Web of Knowledge – Faster and more frequent updates – Encourage use of DataCite DOIs and citation formats – Tracking of citations to their data in the primary research literature – Demonstrate value of citation
  • 21. ©2010ThomsonReuters
  • 22. ©2010ThomsonReuters DATA CITATION BEHAVIOUR Current citation style (in full text of article) Desired/future citation style (as part of 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=G SE11574
  • 23. ©2010ThomsonReuters
  • 24. ©2010ThomsonReuters DATA CITATION INDEX • Discovery of data most important to scholarly research • Data linked to published research literature • Measures of data citation, use and reuse • New metrics for digital scholarship
  • 25. ©2010ThomsonReuters Thank you Nigel Robinson nigel.robinson@thomsonreuters.com