Legal requirement clusters as means to build legally interoperable data bridges between research infrastructures

  • Wolfgang Kuchinke, Toresin Karakoyun
  • November 2015, Institute of Electrical & Electronics Engineers (IEEE)
  • DOI: 10.1109/echallenges.2015.7441063

Software tool to help with rules for legally compliant data sharing

Photo by Luke Chesser on Unsplash

Photo by Luke Chesser on Unsplash

What is it about?

The most important prerequisite for efficient and legally compliant data sharing for research purposes is to guide researchers through the many requirements associated with the sharing of human health data. For this purpose we developed an interactive tool, the Legal Assessment Tool (LAT) that provides researchers interactively with a selection process to provide applicable requirements and recommendations for data access and legally compliant data sharing. A knowledge base was created based on the analysis of data access and sharing conditions of different major research databases in Europe.

Why is it important?

We applied a novel approach that circumvented the problems of legal reasoning for data sharing of personal data. To gather necessary legal and regulatory prerequisites for data sharing we employed concepts from computer science: legal requirement clusters enable legal interoperability between databases for the areas of data protection, data security, Intellectual Property (IP) and security of biosample data. In general, to create applicable rules legal texts need to be interpreted. To avoid this complicated step, we focused on the extraction of access rules and conditions from all data providers involved in the building of data bridges between Europe’s most important research databases. Thereby we moved one step beyond the legal reasoning and use access rules that constitute for themselves valid interpretations of legal requirements.

Perspectives

Wolfgang Kuchinke
Heinrich-Heine-Universitat Dusseldorf

Data sharing for research purposes must be opened for human health data and our tool (LAT) may be one of the means to support this aim, because LAT helps to introduce a culture of responsibility and data governance when dealing with human data that must become the standard for data sharing. Nonetheless, the next step to unburden researchers from the legal constraints of data sharing is the automation of data sharing, to build sufficient automatic controls into the data sharing workflow. For this purpose, authentication, deidentification and anonymisation of data should be integrated into the data sharing workflow supported by monitoring of quality.

Read Publication

http://dx.doi.org/10.1109/echallenges.2015.7441063

The following have contributed to this page: Wolfgang Kuchinke