A Data Citation Roadmap for Scholarly Data Repositories

Authors: Martin Fennera, Merce Crosasb, Jeffrey S. Grethec, David Kennedy, Henning Hermjakobe, Phillippe Rocca-Serraf, Robin Berjong, Sebastian Karcherh, Maryann Martonei, Tim Clark


Abstract: This article presents a practical roadmap for scholarly data repositories to implement data citation in accordance with the Joint Declaration of Data Citation Principles (Data Citation Synthesis Group, 2014), a synopsis and harmonization of the recommendations of major science policy bodies. The roadmap was developed by the Repositories Early Adopters Expert Group, part of the Data Citation Implementation Pilot (DCIP) project (FORCE11, 2015), an initiative of FORCE11.org and the NIH BioCADDIE (2016) program. The roadmap makes 11 specific recommendations, grouped into three phases of implementation: a) required steps needed to support the Joint Declaration of Data Citation Principles, b) recommended steps that facilitate article/data publication workflows, and c) optional steps that further improve data citation support provided by data repositories.


Citation: Fenner, M., Crosas, M., Grethe, J., Kennedy, D., Hermjakob, H., Rocca-Serra, P., … Clark, T. (2016). A Data Citation Roadmap for Scholarly Data Repositories. bioRxiv. https://doi.org/10.1101/097196




Analyzing data citation practices using the Data Citation Index

Authors: Nicolas Robinson-Garcia, Evaristo Jiménez-Contreras, Daniel Torres-Salinas

Abstract: We present an analysis of data citation practices based on the Data Citation Index from Thomson Reuters. This database launched in 2012 aims to link data sets and data studies with citations received from the other citation indexes. The DCI harvests citations to research data from papers indexed in the Web of Science. It relies on the information provided by the data repository as data citation practices are inconsistent or inexistent in many cases. The findings of this study show that data citation practices are far from common in most research fields. Some differences have been reported on the way researchers cite data: while in the areas of Science and Engineering and Technology data sets were the most cited, in Social Sciences and Arts and Humanities data studies play a greater role. A total of 88.1 percent of the records have received no citation, but some repositories show very low uncitedness rates. Although data citation practices are rare in most fields, they have expanded in disciplines such as crystallography and genomics. We conclude by emphasizing the role that the DCI could play in encouraging the consistent, standardized citation of research data; a role that would enhance their value as a means of following the research process from data collection to publication.

Citation: Nicolas Robinson-Garcia, Evaristo Jiménez-Contreras, Daniel Torres-Salinas. (2015).  Analyzing data citation practices using the Data Citation Index. JASIST. doi: http://doi.org/10.1002/asi.23529