Best Practice May Not Be Enough: Variation in Data Citation Using DOIs

Abstract

Citing research data with a persistent identifier, e.g., a digital object identifier (DOI), is typically recognized as part of best practice. However, authors do not always use provided DOIs accurately, or for their intended purpose. This is demonstrated in a recent project conducted by the NSF-funded Measuring the Impact of Curatorial Actions (MICA) project at the University of Michigan and by bibliographers for the Inter-university Consortium for Political and Social Research (ICPSR)’s Bibliography of Data-related Literature. MICA conducted an API query of Dimensions Plus (a large multidisciplinary database with over 69 million publications available for full text search), searching for use of over 11,000 ICPSR study DOIs. The result set of publications citing ICPSR dataset DOIs contained over 2,259 unique hits. The sample discussed in this poster is the large subset of hits that were deemed not collectible by the ICPSR bibliographers, who evaluated the results to determine whether publications met criteria for inclusion in the Bibliography. This poster describes the methodology used to examine the results and the most common reasons why a publication was not added to the Bibliography despite an ICPSR DOI being cited. It also portrays our analysis of the citations in a visual categorization. Based on the results of our analysis, we suggest further exploration of author citation behaviors and more institutional guidance regarding how and when to use data DOIs. Our results also highlight the need for archives to offer other options for citation, so that citation of data analysis can be differentiated from other types of attribution, e.g., brief data mentions, instrument use, or codebook quotations.