Towards a computer-interpretable actionable formal model to encode data governance rules

Towards a computer-interpretable actionable formal model to encode data governance rules Rui Zhao School of Informatics University of Edinburgh Edinburgh, UK s1623641@sms.ed.ac.uk Malcolm Atkinson School of Informatics University of Edinburgh Edinburgh, UK Malcolm.Atkinson@ed.ac.uk Abstract --With the needs of science and business, data sharing and reuse has become an intensive activity for various areas. In many cases, governance imposes rules concerning data use, but there is no existing computational technique to help data-users comply with such rules. We argue that intelligent systems can be used to improve the situation, by recording provenance records during processing, encoding the rules and performing reasoning. We present our initial work, designing formal models for data rules and flow rules and the reasoning system, as the first step towards helping data providers and data users sustain productive relationships. I NTRODUCTION Data ethics and privacy are of rising importance, especially with the establishment of GDPR [1]. Similar issues also apply in research when data from various sources are used as inputs to analyses and simulations. Researchers are aware that there are governance rules applied to the data, but they can easily lose track of the rules when the number of sources becomes large. The large volume of rules brings problem from three aspects: 1) to fully read and understand the rules; 2) to consider the consequence of combining data and their associate rules; 3) to assign rules to output so that results can be used compliantly. One response is to make data open and freely accessible (e.g. This sounds nice but it still leaves rules, for example to properly acknowledge sources and to protect personal and commercially sensitive data, even within collaborating communities [4]. This work has been accepted and should appear in the Proceedings of IEEE eScience 2019 Conference (BC2DC).