INTRODUCTION Data citation should be a necessary corollary of data publication and reuse. Many researchers are reluctant to share their data, yet they are increasingly encouraged to do just that. Reward structures must be in place to encourage data publication, and citation is the appropriate tool for scholarly acknowledgment. Data citation also allows for the identification, retrieval, replication, and verification of data underlying published studies. METHODS This study examines author behavior and sources of instruction in disciplinary and cultural norms for writing style and citation via a content analysis of journal articles, author instructions, style manuals, and data publishers. Instances of data citation are benchmarked against a Data Citation Adequacy Index. RESULTS Roughly half of journals point toward a style manual that addresses data citation, but the majority of journal articles failed to include an adequate citation to data used in secondary analysis studies. DISCUSSION Full citation of data is not currently a normative behavior in scholarly writing. Multiplicity of data types and lack of awareness regarding existing standards contribute to the problem. CONCLUSION Citations for data must be promoted as an essential component of data publication, sharing, and reuse. Despite confounding factors, librarians and information professionals are well-positioned and should persist in advancing data citation as a normative practice across domains. Doing so promotes a value proposition for data sharing and secondary research broadly, thereby accelerating the pace of scientific research
It is expected that authors will provide citations for all papers referenced in their writings. The necessity of providing citations for data is not so widely recognized. Proponents of the data‐sharing movement have advocated the citation of datasets in order to recognize contributions and enhance access. This study examines a sample of papers from the Inter‐University Consortium for Political and Social Research (ICPSR) Bibliography of Data‐Related Literature that are based on secondary analysis of datasets available in the ICPSR data archive to determine the data citation practices of authors. The results indicate that many authors fail to cite the data used in secondary analysis studies. Possible reasons for the dismal state of data citation practices are considered, including the recent introduction of data into the scholarly record and its marginalization as an information format. Updating citation practices to include datasets will support data sharing and foster responsible scholarship.
The undergraduate research experience (URE) provides an opportunity for students to engage in meaningful work with faculty mentors on research projects. An increasingly important component of scholarly research is the application of research data management best practices, yet this often falls out of the scope of URE programs. This article presents a case study of faculty and librarian collaboration in the integration of a library and research data management curriculum into a social work URE research team. Discussion includes reflections on the content and learning outcomes, benefits of a holistic approach to introducing undergraduate students to research practice, and challenges of scale.
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