Towards a computer-interpretable actionable formal model to encode data governance rules
This work addresses the challenge of ensuring data governance compliance for data providers and users, but it is incremental as it presents initial design steps without full implementation or validation.
The paper tackles the problem of data governance compliance by proposing a formal model to encode data use rules, aiming to help data users adhere to governance requirements through intelligent systems that record provenance and perform reasoning.
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.