Background Journals in health sciences increasingly require or recommend that authors deposit the data from their research in open repositories. The rationale for publicly available data is well understood, but many researchers lack the time, knowledge, and skills to do it well, if at all. There are few descriptions of the pragmatic process a researcher author undertakes to complete the open data deposit in the literature.
When my manuscript for a mixed methods study was accepted by a journal that required shared data as condition of publication, I proceeded to comply despite uncertainty with the process.
Purpose The purpose of this work is to describe the experience of an information science researcher and first-time data depositor to complete an open data deposit. The narrative illustrates the questions encountered and choices made in the process.
Process Methods To begin the data deposit process, I found guidance from the accepting journal’s policy and rationale for its shared data requirement. A checklist of pragmatic steps from an open repository provided a framework used to outline and organize the process. Process steps included organizing data files, preparing documentation, determining rights and licensing, and determining sharing and permissions. Choices and decisions included which data versions to share, how much data to share, repository choice, and file naming. Processes and decisions varied between the quantitative and qualitative data prepared.
Results Two datasets and documentation for each were deposited in the Figshare open repository, thus meeting the journal policy requirements to deposit sufficient data and documentation to replicate the results reported in the journal article, and also meeting the deadline to include a Data Availability Statement with the published article.
Conclusion This experience illustrated some practical data sharing issues faced by a librarian author seeking to comply with a journal data sharing policy requirement for publication of an accepted manuscript. Both novice data depositors and data librarians may find this individual experience useful for their own work and the advice they give to others.
Information Visualization for CSV Open Data Files Structure Analysis