DataCite: the Perfect Complement to CrossRef

1. Libraries DataCite:  the Perfect Complement to CrossRef James L. Mullins, PhD Dean of Libraries and Professor CrossRef Annual Meeting Cambridge, MA – November 15, 2011

2. Libraries “I like to think of data in three categories, using a mining metaphor: ‘raw ore’, ‘concentrate’, and ‘virgin metal.’ The question is which data are worth saving and which throwing away?” Arden Bement , executive director, Global Policy Research Institute, Purdue University; retired director, National Science Foundation (NSF). Arden Bement , Remarks before IATUL , June 21 st , 2010, Purdue University, West Lafayette, Indiana. http://docs.lib.purdue.edu/iatul2010/conf/day1/7/

3. Libraries Prolific growth – large and small science Lifeblood – science and engineering research Modeling – demands massive amounts of data Funding Agencies – public accessibility Data/Data Sets

4. Motivation Articles Underlying data Jan Brase – November 2011 No effective way to link between datasets and articles No widely used method to identify datasets No widely used method to cite datasets Underlying data Articles Jan Brase – ORCID Outreach Meeting – September 17 th , 2011 – CERN Libraries

5. Libraries The CrossRef Digital Object Identifier ( DOI®) System identifies Journals. More than 98% of all DOI registered are for scholarly articles. Kuhlmann , Holger ; Freudenthal , Tim; Helmke , Peer; Meggers , Helge (2004): Reconstruction of paleoceanography off NW Africa during the last 40,000 years: influence of local and regional factors on sediment accumulation. Marine Geology, 207(1-4), 209-224, doi:10.1016/j.margeo.2004.03.017

6. Libraries What about Data? Establish easier access to scientific research data on the Internet. Increase acceptance of research data as legitimate, citable contributions to the scientific record. Support data archiving that will permit results to be verified and re-purposed for future study. http://www.datacite.org /

7. Libraries Descriptive Metadata - author (person or corporate), research variables, etc. Subject descriptors - disciplinary taxonomy Digital Object Identifier - persistent identifier Data: Attribution The dataset with DOI: Kuhlmann , H et al. (2009): Age models, iron intensity, magnetic susceptibility records and dry bulk density of sediment cores from around the Canary Islands. doi:10.1594/PANGAEA.727522 ,

8. Libraries Acceptance by research community of the importance of data in research Assignment of authorship/creation (lack of copyright control) – metadata & DOI Citation to dataset by research undertaken and reported – through DataCite Establishment of an h-index for dataset impact Data: Provenance/Citation

9. Libraries CrossRef DOI DataSet Deep Sea Research: Oceanographic Research Papers – Elsevier, Inc.

10. Libraries DOI by DataCite Deep Sea Research: Oceanographic Research Papers – Elsevier, Inc.

11. Technische Informationsbibliothek (TIB) Canada Institute for Scientific and Technical Information (CISTI), California Digital Library, USA Purdue University, USA Office of Scientific and Technical Information ( OSTI), USA Library of TU Delft, The Netherlands Technical Information Center of Denmark The British Library ZB Med, Germany ZBW, Germany Gesis, Germany Library of ETH Zürich L’Institut de l’Information Scientifique et Technique (INIST), France Swedish National Data Service (SND) Australian National Data Service (ANDS) Affiliated members: Digital Curation Center (UK) Microsoft Research Interuniversity Consortium for Political and Social Research (ICPSR) Korea Institute of Science and Technology Information (KISTI) Libraries DataCite Members

12. DataCite Structure Carries International DOI Foundation DataCite California Digital Library and Purdue University Libraries (EZID) Data Centre Data Centre Data Centre Office of Science and Technological Information (OSTI) Data Centre Data Centre Data Centre … Works with Managing Agent (TIB) Member Associate Stakeholder: ICPSR; Microsoft Research In the United States

13. Libraries “I like to think of data in three categories, using a mining metaphor: ‘raw ore’, ‘concentrate’, and ‘virgin metal.’ The question is which data are worth saving and which throwing away?” Arden Bement , executive director, Global Policy Research Institute, Purdue University; retired director, National Science Foundation (NSF). Arden Bement , Remarks before IATUL , June 21 st , 2010, Purdue University, West Lafayette, Indiana. http://docs.lib.purdue.edu/iatul2010/conf/day1/7/

14. Libraries Thank you. Questions? James L. Mullins, Purdue/DataCite: [email protected] Patricia Cruse, CDL/DataCite: [email protected] Sharon Jordan, OSTI/DataCite: [email protected] Jan Brase, TIB/DataCite: [email protected]