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

Rui Zhao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

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.
Original languageEnglish
Title of host publicationProceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21
EditorsZhi-Hua Zhou
PublisherInternational Joint Conferences on Artificial Intelligence Organization
Pages4929-4930
Number of pages2
ISBN (Electronic)978-0-9992411-9-6
DOIs
Publication statusPublished - 19 Aug 2021
Event30th International Joint Conference on Artificial Intelligence - Montreal, Canada
Duration: 19 Aug 202126 Aug 2021
https://ijcai-21.org/

Conference

Conference30th International Joint Conference on Artificial Intelligence
Abbreviated titleIJCAI 2021
Country/TerritoryCanada
CityMontreal
Period19/08/2126/08/21
Internet address

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