Data citation from the perspective of a

scholarly publisher

Lyubomir Penev

TDWG Data Citation Workshop, New Orleans, Oct 2011

ViBRANT

Why cite data and who is interested in that?

Data authors, data managers and their institutions: get credit for their work

Science managers: measure impact of published data through citation metrics

Publishers: drive visits and citations of data to their journals and/or data repositories;

End users of data: facilitate data discovery, use and re-use

Society in general: benefits from public investments in data collecting and maintenance

How to cite data and track citations?

By in-text citation combined with a reference in the reference list (just as with articles)

By using DataCite (or other) DOIs either within the text, or in the references (or both)

By using other permanent identifiers at dataset or single record level (= data usage)

A community agreed norm of a citation format is needed!

The data citation policy of Dryad (www.datadryad.org)

Data citation in Dryad separated from the citation of the scholarly publication

Data authors can differ from the authors of the paper the same data support

Data usage statement recommended (e.g., Data Resources section after the Material and Methods section)

Two components of data citation within a paper: An in-text citation statement containing an in-text reference pointer

that directs the reader to a formal data reference in the paper’s reference list

A formal data reference within the article‘s reference list.

DataCite DOIs assigned to data files within a data package for easy location and tracking

Three main types of data citation

Citation of data firstly published within an article they underpin

OR Citation of data previously published in

association with another articleOR Citation of data previously deposited in a data

repository but never published before in association with an article

Citation of data firstly published within an article

Citation of data previously published in association with an article

Citation of data previously deposited in a data repository but never published before in

association with an article

Conclusions The culture of data publishing and data citing

is still to be developed and accepted by the community

Data Citation metrics lacking; Thomson-Reuters approach to this still unclear!

Data Citation and Data Usage are two sides of the same process

Hence, all interested parties (authors, publishers, data repositories, institutions, end users) should work together towards establishing a stable data publishing and citation landscape!