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Ontology-based update in virtual knowledge graphs via schema mapping recovery
Umeå University, Faculty of Science and Technology, Department of Computing Science.ORCID iD: 0009-0008-5036-2452
Umeå University, Faculty of Science and Technology, Department of Computing Science. Faculty of Engineering, Free University of Bozen-Bolzano, Bolzano, Italy.ORCID iD: 0000-0001-5174-9693
2024 (English)In: Rules and Reasoning: 8th International Joint Conference, RuleML+RR 2024, Bucharest, Romania, September 16–18, 2024, Proceedings, Springer Nature, 2024, p. 59-74Conference paper, Published paper (Refereed)
Abstract [en]

In Virtual Knowledge Graphs (VKGs), access to a relational data source is provided through an ontology, which is linked to the data source via declarative mappings. VKGs stand as a predominant paradigm for the access to (and integration of) heterogeneous data sources. However, little attention has been paid so far to the issue of updates in VKGs expressed over the ontology, which represents a crucial feature for fully managing data sources through the lens of an ontology. In this paper, we consider the problem of updating a VKG instance by specifying a set of insertions and deletions of ontology instances and propagating these updates to the underlying data source through the VKG mapping. We consider ontologies specified in the DL-LiteR lightweight ontology language and study the problem for the case where source queries in mappings are unions of conjunctive queries. We rely on the notion of maximum recovery of VKG mappings, borrowed from the data exchange setting, and propose methods to compute the set of source updates that translate an ontology update with a minimal side-effect, considering both insertions and deletions of multiple ABox assertions.

Place, publisher, year, edition, pages
Springer Nature, 2024. p. 59-74
Series
Lecture Notes in Computer Science, ISSN 03029743, E-ISSN 16113349 ; 15183
Keywords [en]
Knowledge Representation, Ontology-based Data Access, View Updates, Virtual Knowledge Graph (VKG)
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:umu:diva-230585DOI: 10.1007/978-3-031-72407-7_6ISI: 001329984900006Scopus ID: 2-s2.0-85205112822ISBN: 978-3-031-72406-0 (print)ISBN: 978-3-031-72407-7 (electronic)OAI: oai:DiVA.org:umu-230585DiVA, id: diva2:1904205
Conference
8th International Joint Conference on Rules and Reasoning, RuleML+RR 2024, Bucharest, Romania, September 16-18, 2024
Funder
Wallenberg AI, Autonomous Systems and Software Program (WASP)
Note

Included in the following conference series:

International Joint Conference on Rules and Reasoning.

Available from: 2024-10-08 Created: 2024-10-08 Last updated: 2026-04-29Bibliographically approved
In thesis
1. Ontology-based update in virtual knowledge graphs
Open this publication in new window or tab >>Ontology-based update in virtual knowledge graphs
2026 (English)Doctoral thesis, comprehensive summary (Other academic)
Alternative title[sv]
Ontologibaserad uppdatering i virtuella kunskapsgrafer
Abstract [en]

Nowadays, the amount of data generated by users on the Web has increased dramatically, and managing it efficiently is getting more challenging, especially for small or medium-sized organizations. Often, the data to be managed is encoded in a low-level format, requiring domain experts to manually produce a high-level conceptual view from the raw data. A virtual Knowledge Graph (VKG) is a semantic framework that stands as a data integration paradigm aiming to provide convenient, user-friendly access to the data. VKGs, formerly known as ontology-based data access (OBDA), have emerged as an information management system that solves the complex problem of data integration by exposing the end users to an ontology that is typically expressed in some fragment of the Web Ontology Language (OWL2), standardized by the World Wide Web Consortium (W3C). The framework is a virtual approach that typically consists of three main components: an ontology, which is a high-level and conceptual representation of the domain of interest, a set of data sources, and the mapping between the two.

However, with the vision of the Semantic Web, which has consisted of enabling the "Read/Write" Web for structured data, the main focus of research in VKGs has been centered around query-answering which consists of using the ontology layer to extract information specified through a query from the underlying data sources. Yet the problem of updates in VKGs has, however, received little attention and represents an important feature that will enable VKGs to be fully-fledged and, thus, let user fully manage their data from the ontology they are exposed to. This dissertation aims to study and introduce the notions of ontology-based update in the context of VKGs and to study the foundational issues of this extension. In other words, the aim is to study how updates posed over the ontology layer are rewritten into equivalent updates over the underlying data sources.

However, due to the complex nature of VKG mappings, the translation of ontology-based updates is not always deterministic and might lead to extra unintended updates in the knowledge graph, which we refer to as side effects. Considering ontologies specified in DL-LiteR, the formal counterpart of OWL 2 QL, we study how to efficiently translate ontology-based updates by relying on the reverse of VKG mappings. Secondly, based on a given comparison metric for ontology-based update translations, we compute a set of translations with minimum side effects. We also introduce the notion of preference (provided by the user in a declarative format) that can be used to provide a deterministic translation. Finally, we demonstrate the practical feasibility of our approach by implementing the proposed techniques within the Ontop VKG system, translating SPARQL Update operations into SQL statements via R2RML mappings.

Place, publisher, year, edition, pages
Umeå: Umeå University, 2026. p. 50
Series
Report / UMINF, ISSN 0348-0542 ; 26.06
Keywords
computer science, Knowledge Representation, Virtual Knowledge Graph (VKG), Ontology-based Data Access, View Updates, database, graph database
National Category
Artificial Intelligence Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:umu:diva-252705 (URN)978-91-6850-054-6 (ISBN)978-91-6850-055-3 (ISBN)
Public defence
2026-05-26, UB.A.230 (Lindellhallen 3), Umeå, 13:00 (English)
Opponent
Supervisors
Funder
Wallenberg AI, Autonomous Systems and Software Program (WASP)
Note

Link to participate via Zoom: https://umu.zoom.us/j/62610930122.

Available from: 2026-05-04 Created: 2026-04-29 Last updated: 2026-04-30Bibliographically approved

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Wandji, Romuald EsdrasCalvanese, Diego

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