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This was presented at the break-up working group session at TDWG 2010 at Woods Hole

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  1. 1. Biodiversity Information Standards, TDWGGLOBAL Sep. 26 – Oct. 1, 2010, Woods Hole, MA, USABIODIVERSITYINFORMATIONFACILITY Data Citation Mechanism and Services for primary biodiversity data Dr Vishwas Chavan Senior Programme Officer for DIGIT WWW.GBIF.ORG Building the Biodiversity Informatics Commons
  2. 2. Why should I publish data?  Recognition  Opportunities  Investment
  3. 3. Data Publishing Framework Cultural change towards ‘free and open access’ to biodiversity data Addresses social, technical, and policy concerns Answer ‘What is there for me?’ for ALL
  4. 4. Infrastructure and Technical Policy Legal and Political Socio- Economic CulturalChavan and Ingwersen (2009) ,BMC Bioinformatics, 10 (Suppl. 14): S2
  5. 5. DPF: Core Technical Components Data Persistent Citation Identifiers Mechanisms Data Usage IndexChavan and Ingwersen (2009) , BMC Bioinformatics, 10 (Suppl. 14): S2
  6. 6. Call for Data Citation l 1979: Dodd, S. A. (1979). Bibliographic references for numeric social science data files: Suggested guidelines. Journal of the American Society for Information Science, 30 (2): 77-82. l 1990: Dodd, S. A. (1990). Bibliographic references for computer files in the social sciences: A discussion paper. Chapel Hill, NC: Institute for Research in Social Science. Retrieved from l 2006/2007: Altman, M. & King, G. (2007). A proposed standard for the scholarly citation of quantitative data. D-Lib Magazine, 13 (3/4). l 2006: Schneider, J. (2006, Spring). Why we need a data citation standard: Lessons learned from compiling ICPSR’s Bibliography of Data-Related Literature. ICPSR Bulletin. Retrieved from l 2008: Kelly, M. C. (2008). NISO thought leader meeting on research data. Retrieved from l 2009: Green, T. (2009). We need publishing standards for datasets and data tables. OECD Publishing White Paper, OECD Publishing. l 2009: Brase, et al. (2009). Approach for a joint global registration agency for research data. Information Services & Use, 29 (1): 13-27. (i.e, DataCite)
  7. 7. Wish List for Data Citation  Best practice guide for data citation  Persistent identifiers to datasets  Credit to all players from data producers to publishers, aggregators etc.  All levels of granularity and combinations  With or without annotations  Link between traditional literature and data  Coordinated citation support for ALL  Research metrics for datasets
  8. 8. Impact of Data Citation Data Use Data Citation Data Data Preservation Discovery Data Publishing
  9. 9. DataONE/DataCite ExampleDOI resolver and TIB registration 5. URL plus id 4. save full citation EZID resolver and registration service DataCite Member (eg, CDL) 3. citation + 6. full citation URL + id DataONE Coordinating Node metadata DataONE Member catalog (eg, UNM or Node data archive 2. metadata UCSB) (eg, Dryad) + URL + id 7. full citation get unique id string 1. data + metadata Research scientist (opt) CDL-hosted EZID id get unique id string minting service
  10. 10. Citation modell When using data from Dryad, please cite the original article. l Sidlauskas, B. 2007. Testing for unequal rates of morphological diversification in the absence of a detailed phylogeny: a case study from characiform fishes. Evolution 61: 299–316.l Additionally, please cite the Dryad data package. The citation should include the following elements: l Author(s) l The date on which the data was deposited l The name of the data file, if applicable l The title of the data package, which in Dryad is always "Data from: [Article name]" l The name "Dryad Digital Repository" l The data identifierl For example: l Sidlauskas, B. 2007. Data from: Testing for unequal rates of morphological diversification in the absence of a detailed phylogeny: a case study from characiform fishes. Dryad Digital Repository. doi:10.5061/dryad.20
  11. 11. Data Citation Mechanism & Service  Deep data citation mechanism  Recognise ALL with their roles  Multilayer citation – producer, publisher, aggregator  Citations within citations  Data Citation Service  Resolve citation any time  Discover the underlined data
  12. 12. Data Citation: Challenges  Dealing with dynamic streaming data?  Resolving to human or machine interpretable description of object?  Need for registry of name spaces?  Can metadata standards support multiple GUIDs?  Failure to enforce data citation as mandatory step in Publishing cycle
  13. 13. Data Paper: Current Indian J.Recognising PhytoKeys Mar. Sci. BiologyData Discovery DoI Publication Acceptance GBRDS Journal Revision System Peer Review GBIF Metadata Submission Repository Registry auto conversion to manuscript Distributed Persistent Metadata Identifiers Catalogues Metadata Authors
  14. 14. Data Publishing together with Scholarly Publishing!Email: