New Video Shows How to Cite Data

By properly citing data in research publications, it not only acknowledges sources, it also makes it easier for others to discover, (re-)use, and re-purpose the data. Data citation is quickly becoming best practice across all disciplines. This new video tutorial shows data users how to retrieve citation information directly from UK Data Service resources. Although this video particularly focuses on how-to-cite datasets from the UK Data Service, it covers general principles of data citation, including what it is and why it is important.

In addition to the UK Data Service website guidance, other data centers and repositories also provide similar data citation guidance, including the Inter-university Consortium for Political and Social Research (ICPSR).

 

Informal Review of Thomson-Reuters Data Citation Index

The Thomson-Reuters Data Citation Index (DCI) has been up and running for just over a year. Amy West posted a blog reviewing the Data Citation Index (DCI) based on a trial at her institution, the University of Minnesota (UMN). West says in her blog that, “(w)hat makes the DCI interesting is that puts datasets and journal literature into a single platform, namely Thomson-Reuter’s Web of Science (WoS). Within the overall WoS, there is a core collection that constitutes the default search for subscribers. We know from our own statistics as well as vendor supplied statistics that our users do indeed go to WoS.”

Her blog post includes a link to notes with more details about the DCI trial.

Continue reading her post…. 

 

Endorse the Joint Declaration of Data Citation Principles

On behalf of the Data Citation Synthesis Group of Force 11 (the Future of Research Communication and e-Scholarship), Dr. Simon Hodson, Executive Director of CODATA, calls on all individuals and organizations that care about the place of data in research communications to endorse the Joint Declaration of Data Citation Principles.

Many groups, including the CODATA-ICSTI Task Group on Data Citation, have contributed to the development of these principles.

Survey Research on Data Publication Practices and Perceptions by CDL

Asking researchers what they would expect and want from a data publication

The California Digital Library has opened a survey of researcher perceptions and practices around data publication. The library community has been productively discussing these issues for some time. The CDL research team hopes to contribute by asking researchers directly what they would expect and want from a data publication.

You can find more information about the CDL survey research here and take a survey.

Draft Declaration of Data Citation Principles

Draft Declaration of Data Citation Principles released for public comment

The members of Force 11 (the Future of Research Communications and e-Scholarship) have been working on data citation principles and guidelines and they internationally came together to forge a synthesis set of data citation principles. The working group has completed its work and announced the release of a Draft Declaration of Data Citation Principles for public comment.

The draft can be found at: http://www.force11.org/datacitation

The public comment period will run through the end of this December, at which point feedback will be incorporated and a released version of the declaration generated and promulgated widely. Public endorsement of the principles will be sought at that time.

Data Citation Developments | Blog Post

Data Citation Developments, Blog Post by John Kratz, California Digital Library

This is a nice sum-up of recent discussions and activities centering on the topic of data citation.

Citation is a defining feature of scholarly publication and if we want to say that a dataset has been published, we have to be able to cite it. The purpose of traditional paper citations– to recognize the work of others and allow readers to judge the basis of the author’s assertions– align with the purpose of data citations. Check out previous posts on the topic here.

Although in the past, datasets and databases have usually been mentioned haphazardly, if at all, in the body of a paper and left out of the list of references, this no longer has to be the case.

Last month, there was quite a bit of activity on the data citation front:

Continue reading this blog post….

Data Reuse and the Open Data Citation Advantage | PeerJ

Data Reuse and the Open Data Citation Advantage, article by Heather A. Piwowar​ and Todd J. Vision

Share Early. Share Openly. Share Often. If you want more citations, share your data now! It’s the message we receive from a newly published article by Piwowar and Vision. They present empirical findings supporting a robust citation benefit from open data.

Conclusion. After accounting for other factors affecting citation rate, we find a robust citation benefit from open data, although a smaller one than previously reported. We conclude there is a direct effect of third-party data reuse that persists for years beyond the time when researchers have published most of the papers reusing their own data. Other factors that may also contribute to the citation benefit are considered. We further conclude that, at least for gene expression microarray data, a substantial fraction of archived datasets are reused, and that the intensity of dataset reuse has been steadily increasing since 2003.

A full article is available at: https://peerj.com/articles/175/

Cite this article: Piwowar HA, Vision TJ. (2013) Data reuse and the open data citation advantage. PeerJ 1:e175 http://dx.doi.org/10.7717/peerj.175