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

1. Biodiversity Information Standards, TDWG
GLOBAL Sep. 26 – Oct. 1, 2010, Woods Hole, MA, USA
BIODIVERSITY
INFORMATION
FACILITY
Data Citation Mechanism and
Services for primary
biodiversity data
Dr Vishwas Chavan
Senior Programme Officer for DIGIT
vchavan@gbif.org
WWW.GBIF.ORG
Building the Biodiversity Informatics Commons

2. Why should I publish data?
 Recognition
 Opportunities
 Investment

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. Infrastructure
and Technical
Policy
Legal and
Political
Socio-
Economic
Cultural
Chavan and Ingwersen (2009) ,
BMC Bioinformatics, 10 (Suppl. 14): S2

5. DPF: Core Technical Components
Data
Persistent
Citation
Identifiers
Mechanisms
Data Usage Index
Chavan and Ingwersen (2009) , BMC Bioinformatics, 10 (Suppl. 14): S2

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 http://people.virginia.edu/~pm9k/info/compRef.html
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
http://www.icpsr.umich.edu/files/ICPSR/org/publications/bulletin/2006-Q1.pdf.
l 2008: Kelly, M. C. (2008). NISO thought leader meeting on research data.
Retrieved from http://www.niso.org/topics/tl/NISOTLDataReportDraft.pdf.
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. 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. Impact of Data Citation
Data Use Data Citation
Data Data
Preservation Discovery
Data
Publishing

9. DataONE/DataCite Example
DOI 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. Citation model
l 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 identifier
l 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

13. 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

14. 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

15. Data Paper:
Current Indian J.
Recognising PhytoKeys
Mar. Sci.
Biology
Data 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

16. Data Publishing
together with
Scholarly Publishing!
Email: vchavan@gbif.org