An Automated Framework for Supporting Data-Governance Rule Compliance in Decentralized MIMO Contexts

TL;DR

This paper introduces Dr.Aid, an AI framework that automates compliance checking of data governance rules in decentralized MIMO data-flow contexts using formal logic and real-world provenance data.

Contribution

It presents a novel logic-based framework for automated compliance verification tailored to decentralized MIMO data processes, integrating formal rule modeling and reasoning.

Findings

Effective compliance checking demonstrated on real-world datasets

Framework supports complex data flow and rule propagation scenarios

Enhances automation in data governance in decentralized environments

Abstract

We propose Dr.Aid, a logic-based AI framework for automated compliance checking of data governance rules over data-flow graphs. The rules are modelled using a formal language based on situation calculus and are suitable for decentralized contexts with multi-input-multi-output (MIMO) processes. Dr.Aid models data rules and flow rules and checks compliance by reasoning about the propagation, combination, modification and application of data rules over the data flow graphs. Our approach is driven and evaluated by real-world datasets using provenance graphs from data-intensive research.