Fröhlich, N., Meier, A., Pardal, N. et al. (1 more author) (2025) A logic-based framework for database repairs. In: Proceedings of the 22nd International Conference on Principles of Knowledge Representation and Reasoning, KR 2025. 22nd International Conference on Principles of Knowledge Representation and Reasoning (KR2025), 11-17 Nov 2025, Melbourne, Australia. International Joint Conferences on Artificial Intelligence Organization. ISBN: 9781956792089. ISSN: 2334-1033. EISSN: 2334-1025.
Abstract
We introduce a general abstract framework for database repairs, where the repair notions are defined using formal logic. We distinguish between integrity constraints and so-called query constraints. The former are used to model consistency and desirable properties of the data (such as functional dependencies and independencies), while the latter relate two database instances according to their answers to the query constraints. The framework allows for a distinction between hard and soft queries, allowing the answers to a core set of queries to be preserved, as well as defining a distance between instances based on query answers. We illustrate how different repair notions from the literature can be modelled in our framework. The framework generalises both set-based and cardinality based repairs to semiring annotated databases. Finally, we initiate a complexity-theoretic analysis of consistent query answering and checking existence of a repair in our setting.
Metadata
| Item Type: | Proceedings Paper |
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| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | © 2025 International Joint Conferences on Artificial Intelligence Organization. Reproduced in accordance with the publisher's self-archiving policy. |
| Keywords: | Database Repairs; Semiring; Complexity |
| Dates: |
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| Institution: | The University of Sheffield |
| Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
| Funding Information: | Funder Grant number DEUTSCHE FORSCHUNGSGEMEINSCHAFT / DFG UNSPECIFIED |
| Date Deposited: | 11 Nov 2025 16:00 |
| Last Modified: | 11 Nov 2025 16:00 |
| Status: | Published |
| Publisher: | International Joint Conferences on Artificial Intelligence Organization |
| Refereed: | Yes |
| Identification Number: | 10.24963/kr.2025/32 |
| Related URLs: | |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:234246 |

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