Community curation in open dataset repositories: insights from Zenodo

Abstract

The increasing concern for the availability of scientific data has resulted in a number of initiatives promoting the archival and curation of datasets as a legitimate research outcome. Among them, dataset repositories fill the gap of providing long-term preservation of diverse kinds of data along with its meta-descriptions, and support citation. Unsurprisingly, the concern for quality arises as in the publication of papers. However, repositories support a larger variety of use cases, and many of them implement minimal control on the data uploaded by users. An approach to tackle with quality control in repositories is that of letting communities of users to filter the relevant resources for them, at the same time providing some form of trust to users of the data. However, there is a lack of knowledge of the extent to which this social approach that relies on communities self-organizing actually contributes to the effective organization inside repositories. This paper reports the results of a study on the Zenodo repository, describing its main contents and how communities have emerged naturally around the deposited contents.