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

Abstract: With the needs of science and business, data sharing and re-use 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.

This paper is submitted and accepted to BC2DC workshop at IEEE eScience Conference 2019.

You can download the preprint of the paper from here.

The presentation of the talk gave at San Diego can be downloaded from here.