| dc.description.abstract | ‘Which requirements should a data repository meet to satisfy the FAIR principles?’ is the main research question in this thesis. Whereas FAIR stands for: Findability, Accessibility, Interoperability and Reusability. This study is relevant since a data-driven economy and a digital mindset requires for companies and academia to extend their existing meta data management approaches. Regarding (open) data repositories it is no longer enough to take care of the quantitative part; the amount of data, sources and/or publications in the repository. Good data management becomes more and more important. To answer the main research question, we distinguish three main parts: A systematic Literature Research on the FAIR concepts (RQ1), the context where FAIR can be applied in (RQ2), and the requirements for measuring whether data repositories are FAIR (RQ3). The first research question results in four definitions on the FAIR concepts. Thereby, the main result of this literature research is that Reusability must be resultant of the other three, which implies: (F + A + I)/3 = R. Together with the result of research question 3, a set of Meta Data Attributes, these definitions and relation form the basis for the Reference Model (Artifact 2). The main goal of the model is to provide a step-by-step set of activities to ensure a data repository contains all aspects to measure FAIR, with the focus on comprehensibility, and accessibility in public and private sector. The context where this model can be applied in is the Data Scouting Process (Artifact 1). The main goal of this artifact is to determine the place of FAIR in the context of open data projects. We set up this artifact, as result of research question 2, based on a case study at Berenschot Intellerts. During this case study, we also applied the reference model into practice. The artifacts are evaluated based on iterative expert evaluation at Berenschot Intellerts (Artifact 1), interviews at CBS and Gemeente van Amsterdam (Artifact 2), and a survey among experts from business and academia (Artifact 2). | |
