Jones, S., Pergl, R., Hooft, R., Miksa, T., Samors, R., Ungvari, J., Davis, R. I., & Lee, T. (2020). Data Management Planning: How Requirements and Solutions are Beginning to Converge. International Journal of Big Data Intelligence, 2(1–2), 208–219. https://doi.org/10.1162/dint_a_00043
Mechanical Engineering; Industrial and Manufacturing Engineering; FAIR; Strategy and Management; Metals and Alloys; Data management; Data stewardship; Machine-actionable; DMP tools
Effective stewardship of data is a critical precursor to making data FAIR. The goal of this paper is to bring an overview of current state of the art of data management and data stewardship planning solutions (DMP). We begin by arguing why data management is an important vehicle supporting adoption and implementation of the FAIR principles, we describe the background, context and historical development, as well as major driving forces, being research initiatives and funders. Then we provide an overview of the current leading DMP tools in the form of a table presenting the key characteristics. Next, we elaborate on emerging common standards for DMPs, especially the topic of machine-actionable DMPs. As sound DMP is not only a precursor of FAIR data stewardship, but also an integral part of it, we discuss its positioning in the emerging FAIR tools ecosystem. Capacity building and training activities are an important ingredient in the whole effort. Although not being the primary goal of this paper, we touch also the topic of research workforce support, as tools can be just as much effective as their users are competent to use them properly. We conclude by discussing the relations of DMP to FAIR principles, as there are other important connections than just being a precursor.