research-article

BUNNI: Learning Repair Actions in Rule-driven Data Cleaning

Authors:

Giansalvatore Mecca,

Donatello Santoro,

Enzo VeltriAuthors Info & Claims

ACM Journal of Data and Information Quality, Volume 16, Issue 2

Article No.: 12, Pages 1 - 31

https://doi.org/10.1145/3665930

Published: 24 June 2024 Publication History

Abstract

In this work, we address the challenging and open problem of involving non-expert users in the data repairing problem as first-class citizens. Despite a large number of proposals that have been devoted to cleaning data from the point of view of expert users (IT staff and data scientists), there is a lack of studies from the perspective of non-expert ones. Given a set of available data quality rules, we exploit machine learning techniques to guide the user to identify the dirty values for each violation and repair them. We show that with a low user effort, it is possible to identify the values in tuples that can be trusted and the ones that are most likely errors. We show experimentally how this machine learning approach leads to a unique clean solution with high quality in scenarios where other approaches fail.

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Cited By

Boeckling TBronselaer A(2025)Cleaning data with SwipeJournal of Data and Information Quality10.1145/3712205Online publication date: 14-Feb-2025
https://dl.acm.org/doi/10.1145/3712205
Nasfi Rde Tré GBronselaer A(2025)Improving Data Cleaning by Learning From Unstructured Textual DataIEEE Access10.1109/ACCESS.2025.354395313(36470-36491)Online publication date: 2025
https://doi.org/10.1109/ACCESS.2025.3543953

Index Terms

BUNNI: Learning Repair Actions in Rule-driven Data Cleaning

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Published In

cover image Journal of Data and Information Quality

Journal of Data and Information Quality Volume 16, Issue 2

June 2024

135 pages

EISSN:1936-1963

DOI:10.1145/3613602

Editor:
Felix Naumann
Hasso Plattner Institute, Germany

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Publication History

Published: 24 June 2024

Online AM: 25 May 2024

Accepted: 15 May 2024

Revised: 06 February 2024

Received: 04 May 2023

Published in JDIQ Volume 16, Issue 2

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Cited By

Boeckling TBronselaer A(2025)Cleaning data with SwipeJournal of Data and Information Quality10.1145/3712205Online publication date: 14-Feb-2025
https://dl.acm.org/doi/10.1145/3712205
Nasfi Rde Tré GBronselaer A(2025)Improving Data Cleaning by Learning From Unstructured Textual DataIEEE Access10.1109/ACCESS.2025.354395313(36470-36491)Online publication date: 2025
https://doi.org/10.1109/ACCESS.2025.3543953

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