0
CrossRef Annual Meeting         Cambridge, MA – November 15, 2011DataCite: the PerfectComplement to CrossRef James L. Mull...
“I like to think of data in three categories,using a mining metaphor: ‘raw ore’,‘concentrate’, and ‘virgin metal.’ Theques...
Data/Data Sets•Prolific growth – large and small science•Lifeblood – science and engineeringresearch•Modeling – demands ma...
Motivation                             – No effective way to link                  Articles     between datasets and artic...
The CrossRef Digital Object Identifier (DOI®)System identifies Journals. More than 98% of all DOIregistered are for schola...
•Establish easier access to scientific research data on the   Internet.•Increase acceptance of research data as legitimate...
• Descriptive Metadata - author (person   or corporate), research variables, etc.• Subject descriptors - disciplinary   ta...
• Acceptance by research community of   the importance of data in research• Assignment of authorship/creation (lack   of c...
Deep Sea Research: Oceanographic Research Papers –Elsevier, Inc.    CrossRef DOI                   DataSet                ...
Deep Sea Research: Oceanographic Research Papers –Elsevier, Inc.          DOI by DataCite                                 ...
DataCite Members•   Technische Informationsbibliothek (TIB)•   Canada Institute for Scientific and Technical Information (...
DataCite Structure                        International DOIIn the                     FoundationUnited                Memb...
“I like to think of data in three categories,using a mining metaphor: ‘raw ore’,‘concentrate’, and ‘virgin metal.’ Theques...
Thank you.Questions?James L. Mullins, Purdue/DataCite: jmullins@purdue.eduPatricia Cruse, CDL/DataCite: Patricia.Cruse@uco...
Upcoming SlideShare
Loading in...5
×

DataCite: the Perfect Complement to CrossRef

1,363

Published on

Published in: Education, Technology
1 Comment
2 Likes
Statistics
Notes
  • Video recording of this presentation is now available on River Valley TV:
    http://river-valley.tv/datacite-the-perfect-complement-to-crossref/
       Reply 
    Are you sure you want to  Yes  No
    Your message goes here
No Downloads
Views
Total Views
1,363
On Slideshare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
13
Comments
1
Likes
2
Embeds 0
No embeds

No notes for slide

Transcript of "DataCite: the Perfect Complement to CrossRef"

  1. 1. CrossRef Annual Meeting Cambridge, MA – November 15, 2011DataCite: the PerfectComplement to CrossRef James L. Mullins, PhD Dean of Libraries and Professor Libraries
  2. 2. “I like to think of data in three categories,using a mining metaphor: ‘raw ore’,‘concentrate’, and ‘virgin metal.’ Thequestion is which data are worth savingand which throwing away?” Arden Bement, Remarks before IATUL, June 21st, 2010, Purdue University, West Lafayette, Indiana. http://docs.lib.purdue.edu/iatul2010/conf/day1/7/ Libraries
  3. 3. Data/Data Sets•Prolific growth – large and small science•Lifeblood – science and engineeringresearch•Modeling – demands massive amounts of data•Funding Agencies – public accessibility Libraries
  4. 4. Motivation – No effective way to link Articles between datasets and articles Articles – No widely used method to identify datasets – No widely used method toUnderlying cite datasetsUnderlying datadata Jan Brase – ORCID Outreach Meeting – September 17th, 2011 – CERN Jan Brase – November 2011 Libraries
  5. 5. The CrossRef Digital Object Identifier (DOI®)System identifies Journals. More than 98% of all DOIregistered are for scholarlyarticles.Kuhlmann, Holger; Freudenthal, Tim; Helmke, Peer; Meggers,Helge (2004): Reconstruction of paleoceanography off NWAfrica during the last 40,000 years: influence of local andregional factors on sediment accumulation. Marine Geology,207(1-4), 209-224, doi:10.1016/j.margeo.2004.03.017 Libraries
  6. 6. •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/ Libraries
  7. 7. • Descriptive Metadata - author (person or corporate), research variables, etc.• Subject descriptors - disciplinary taxonomy• Digital Object Identifier - persistent identifierThe dataset with DOI:Kuhlmann, H et al. (2009): Age models, iron intensity,magnetic susceptibility records and dry bulk densityof sediment cores from around the Canary Islands.doi:10.1594/PANGAEA.727522, Libraries
  8. 8. • 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 Libraries
  9. 9. Deep Sea Research: Oceanographic Research Papers –Elsevier, Inc. CrossRef DOI DataSet Libraries
  10. 10. Deep Sea Research: Oceanographic Research Papers –Elsevier, Inc. DOI by DataCite Libraries
  11. 11. DataCite Members• 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
  12. 12. DataCite Structure International DOIIn the FoundationUnited MemberStates DataCite Managing Agent (TIB) California Digital Office of Science and Associate Library and Technological Stakeholder: Purdue University Information (OSTI) ICPSR; Libraries (EZID) Microsoft … Research Works Data Centre Data Centre Data Centre Data Centre Data Centre Data Centre with
  13. 13. “I like to think of data in three categories,using a mining metaphor: ‘raw ore’,‘concentrate’, and ‘virgin metal.’ Thequestion is which data are worth savingand which throwing away?” Arden Bement, Remarks before IATUL, June 21st, 2010, Purdue University, West Lafayette, Indiana. http://docs.lib.purdue.edu/iatul2010/conf/day1/7/ Libraries
  14. 14. Thank you.Questions?James L. Mullins, Purdue/DataCite: jmullins@purdue.eduPatricia Cruse, CDL/DataCite: Patricia.Cruse@ucop.eduSharon Jordan, OSTI/DataCite: JordanS@osti.govJan Brase, TIB/DataCite: Jan.Brase@tib.uni-hannover.de Libraries
  1. A particular slide catching your eye?

    Clipping is a handy way to collect important slides you want to go back to later.

×