The following article was published today by Data Science Journal.
Data Science Journal
The ability to reuse research data is now considered a key benefit for the wider research community. Researchers of all disciplines are confronted with the pressure to share their research data so that it can be reused. The demand for data use and reuse has implications on how we document, publish and share research in the first place, and, perhaps most importantly, it affects how we measure the impact of research, which is commonly a measurement of its use and reuse. It is surprising that research communities, policy makers, etc. have not clearly defined what use and reuse is yet.
We postulate that a clear definition of use and reuse is needed to establish better metrics for a comprehensive scholarly record of individuals, institutions, organizations, etc. Hence, this article presents a first definition of reuse of research data. Characteristics of reuse are identified by examining the etymology of the term and the analysis of the current discourse, leading to a range of reuse scenarios that show the complexity of today’s research landscape, which has been moving towards a data-driven approach. The analysis underlines that there is no reason to distinguish use and reuse. We discuss what that means for possible new metrics that attempt to cover Open Science practices more comprehensively. We hope that the resulting definition will enable a better and more refined strategy for Open Science.
Direct to Full Text Article