IJCAI 2021poster0 citations
An Automated Framework for Supporting Data-Governance Rule Compliance in Decentralized MIMO Contexts
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.
Multidisciplinary Topics and Applications: Security and PrivacyPlanning and Scheduling: Model-Based ReasoningAgent-based and Multi-agent Systems: Normative systems
BibTeX
@inproceedings{ijcai2021p696,
title = {An Automated Framework for Supporting Data-Governance Rule Compliance in Decentralized MIMO Contexts},
author = {Zhao, Rui},
booktitle = {Proceedings of the Thirtieth International Joint Conference on
Artificial Intelligence, {IJCAI-21}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Zhi-Hua Zhou},
pages = {4929--4930},
year = {2021},
month = {8},
note = {Doctoral Consortium},
doi = {10.24963/ijcai.2021/696},
url = {https://doi.org/10.24963/ijcai.2021/696},
}