To do or not to do? – Decision-making trees and tools for legal questions in research data management (RDM)

In data management researchers and research support staff must deal with organizational, technical and legal questions. Examples are the data collection process, secure storage of personal information or the legal bases to process such data. Some of these questions have been answered in papers and presentations or have made their way into (commented) checklists. On the other hand, some questions are more complex, because they consist of simpler, more detailed and interdependent questions. Areas where this is particularly relevant are legal issues, such as data protection, intellectual property rights and contractual arrangements of various kinds. Now, even if these simpler questions increase the understanding of challenges and support the implementation of adequate data management means, legal aspects in general remain problematic for researchers and research support staff to tackle. In order to facilitate decision-making, the German project group KuRWORK (GESIS, Technical Information Library – TIB, Hannover, Science Center Berlin - WZB) evaluated decision-making trees designed by the DataJus project (Lauber-Rönsberger et al., Technical University, Dresden) by testing them against cases of existing data from research projects. The aim of the KuRWORK project is to improve these decision-making trees and to make them accessible in a more dynamic way. In this paper we present the original ideas, our improvements and Xerte (https://www.xerte.org.uk/) and HP5 (https://h5p.org/) as tools to map the decision trees.