An examination of research data sharing and re-use: implications for data citation practice

Abstract

This study examines characteristics of data sharing and data re-use in Genetics and Heredity, where data citation is most common. This study applies an exploratory method because data citation is a relatively new area. The Data Citation Index (DCI) on the Web of Science was selected because DCI provides a single access point to over 500 data repositories worldwide and to over two million data studies and datasets across multiple disciplines and monitors quality research data through a peer review process. We explore data citations for Genetics and Heredity, as a case study by examining formal citations recorded in the DCI and informally by sampling a selection of papers for implicit data citations within publications. Citer-based analysis is conducted in order to remedy self-citation in the data citation phenomena. We explore 148 sampled citing articles in order to identify factors that influence data sharing and data re-use, including references, main text, supplementary data/information, acknowledgments, funding information, author information, and web/author resources. This study is unique in that it relies on a citer-based analysis approach and by analyzing peer-reviewed and published data, data repositories, and citing articles of highly productive authors where data sharing is most prevalent. This research is intended to provide a methodological and practical contribution to the study of data citation.

Informal data citation for data sharing and reuse is more common than formal data citation in biomedical fields

“…Table summarizes the indicator terms used, which consists of those identified by Park and Wolfram () and includes additional terms identified during the searching of each article. Commonly used indicator terms and phrases for data sharing and reuse in the examined articles were “dataset,” “database,” ”.edu,” “obtained from,” ”.gov,” “accession,” “suppl,” “Suppl,” “commercial,” and “National Institutes of Health.” Figure summarizes the terms and phrases used in data sharing and reuse and their frequency.…”

“…Informal references to data sets retrieved from the main text also were higher than formal citation counts. Park and Wolfram () found that informal data citation is common in the Genetics and Heredity subject category in the DCI. These informal occurrences provide a direct indication of data reuse, especially in sections of the main text of publications such as the Methods section, where data collection or data analysis are described.…”

Reuse Remix Recycle

“…However, analyses of data citation demonstrate that their use is as yet limited: research data commonly go uncited (Peters et al 2016:740), explicit data citations in the reference sections of publications are rare, and where reference is made at all, it is to the title of the dataset in the body of the essay (Mooney and Newton 2012:7) or in the acknowledgments or supplementary materials. The lack or informality of data citation makes the identification and documentation of reuse difficult (Park and Wolfram 2017:457), and a brief overview of archaeological data citation suggests that the situation is much the same. For instance, a survey of Archaeology Data Service datasets indexed in the DCI indicates that 56 of 476 datasets (as of August 2017) had been cited, although only 12 had been cited more than once.…”

Creating Data Citation Templates for Economics

“…Unfortunately, citing data is not an accepted or routine practice in the same way as it is for more traditional sources, and, at most, attribution is often included informally as a note below a graph or figure. While there are many reasons for this, including a broader discussion on data sharing in general, one major issue is the lack of universally accepted citation standards (Park & Wolfram, 2017). Other non-traditional source types such as musical recordings and YouTube videos receive acknowledgment in many styles, but formatting standards for data -which often serves as the basis for numerous scholarly outputs -are rare.…”