Exploring Data Publishing Process Options for Data Papers and Datasets

Abstract

More research datasets are increasingly published in data journals and the research community. Data journals publish data papers and corresponding research datasets through peer review. Data journals aim for data papers and datasets to be findable, accessible, interoperable, and reusable by requiring authors to deposit the dataset in the public data repository. Many authors publish research and data papers as preprints on Preprint servers. There may be different peer review and publishing process options during the data publishing process among data journals, data repositories, and Preprint servers. However, these publishing options for data papers and datasets have not been studied much in the literature. This paper explores different data publishing process options using the Publish-Review-Curate approach. This paper also presents the essential concepts of the given process options and discusses the trade-offs of the options. To evaluate the proposed process options, we assembled the opinions of some editors and staff working on the data journals. The suggested and reviewed process models would offer insight into the potential for collaborative data publishing among participating parties. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.