research-article

Contextual Intelligence for Unified Data Governance

Authors:

Eser Kandogan, and

Mary RothAuthors Info & Claims

aiDM'18: Proceedings of the First International Workshop on Exploiting Artificial Intelligence Techniques for Data Management

June 2018

Article No.: 2, Pages 1 - 9

https://doi.org/10.1145/3211954.3211955

Published: 10 June 2018 Publication History

Abstract

Current data governance techniques are very labor-intensive, as teams of data stewards typically rely on best practices to transform business policies into governance rules. As data plays an increasingly key role in today's data-driven enterprises, current approaches do not scale to the complexity and variety present in the data ecosystem of an enterprise as an increasing number of data requirements, use cases, applications, tools and systems come into play. We believe techniques from artificial intelligence and machine learning have potential to improve discoverability, quality and compliance in data governance. In this paper, we propose a framework for 'contextual intelligence', where we argue for (1) collecting and integrating contextual metadata from variety of sources to establish a trusted unified repository of contextual data use across users and applications, and (2) applying machine learning and artificial intelligence techniques over this rich contextual metadata to improve discoverability, quality and compliance in governance practices. We propose an architecture that unifies governance across several systems, with a graph serving as a core repository of contextual metadata, accurately representing data usage across the enterprise and facilitating machine learning, We demonstrate how our approach can enable ML-based recommendations in support of governance best practices.

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Cited By

Feng YRahman SFeng AChen VKandogan E(2024)CMDBench: A Benchmark for Coarse-to-fine Multimodal Data Discovery in Compound AI SystemsProceedings of the Conference on Governance, Understanding and Integration of Data for Effective and Responsible AI10.1145/3665601.3669846(16-25)Online publication date: 9-Jun-2024
https://dl.acm.org/doi/10.1145/3665601.3669846
Nasir SKhan RBai S(2024)Ethical Framework for Harnessing the Power of AI in Healthcare and BeyondIEEE Access10.1109/ACCESS.2024.336991212(31014-31035)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3369912
Chandra YPrabowo HGaol FPurwandari B(2023)Control and Data Integrity are Important Factors of Data Governance Technology2023 10th International Conference on ICT for Smart Society (ICISS)10.1109/ICISS59129.2023.10291563(1-6)Online publication date: 6-Sep-2023
https://doi.org/10.1109/ICISS59129.2023.10291563

Index Terms

Contextual Intelligence for Unified Data Governance
1. Applied computing
  1. Enterprise computing
    1. Enterprise data management
    2. IT governance
2. Information systems

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cover image ACM Conferences

aiDM'18: Proceedings of the First International Workshop on Exploiting Artificial Intelligence Techniques for Data Management

June 2018

34 pages

ISBN:9781450358514

DOI:10.1145/3211954

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGMOD: ACM Special Interest Group on Management of Data

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Published: 10 June 2018

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SIGMOD/PODS '18: International Conference on Management of Data

June 10, 2018

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aiDM'18 Paper Acceptance Rate 5 of 8 submissions, 63%;

Overall Acceptance Rate 19 of 26 submissions, 73%

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Cited By

Feng YRahman SFeng AChen VKandogan E(2024)CMDBench: A Benchmark for Coarse-to-fine Multimodal Data Discovery in Compound AI SystemsProceedings of the Conference on Governance, Understanding and Integration of Data for Effective and Responsible AI10.1145/3665601.3669846(16-25)Online publication date: 9-Jun-2024
https://dl.acm.org/doi/10.1145/3665601.3669846
Nasir SKhan RBai S(2024)Ethical Framework for Harnessing the Power of AI in Healthcare and BeyondIEEE Access10.1109/ACCESS.2024.336991212(31014-31035)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3369912
Chandra YPrabowo HGaol FPurwandari B(2023)Control and Data Integrity are Important Factors of Data Governance Technology2023 10th International Conference on ICT for Smart Society (ICISS)10.1109/ICISS59129.2023.10291563(1-6)Online publication date: 6-Sep-2023
https://doi.org/10.1109/ICISS59129.2023.10291563

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