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Towards techniques for updating virtual knowledge graphs
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.ORCID iD: 0000-0003-0632-0294
Umeå University, Faculty of Science and Technology, Department of Computing Science. Research Centre for Knowledge and Data, Faculty of Engineering, Free University of Bozen-Bolzano, Bolzano, Italy.ORCID iD: 0000-0001-5174-9693
2023 (English)In: Proceedings of the 17th International Rule Challenge and 7th Doctoral Consortium @ RuleML+RR 2023 (RuleML+RR-Companion 2023), Oslo, Norway, 18 - 20 September, 2023 / [ed] Jan Vanthienen; Tomáš Kliegr; Paul Fodor; Davide Lanti; Dörthe Arndt; Egor V. Kostylev; Theodoros Mitsikas; Ahmet Soylu, CEUR-WS , 2023, article id 9284Conference paper, Published paper (Refereed)
Abstract [en]

The field of Virtual Knowledge Graphs (VKGs) continues to grow in both academic and applied contexts. Yet, the issue of updates in VKG systems has not yet received adequate attention, although it is crucial to manage data modifications at the data source level through the lens of an ontology. In this paper, we focus on VKGs whose ontology is specified in the lightweight ontology language DL-LiteA, and we propose diverse settings and research directions we intend to explore to address the challenge of translating ontology-based updates into updates at the level of data sources. We also pay attention to the important problem of automated analysis of mappings, which plays a major role when it comes to reformulating ontology-based update requests into update requests over the data sources.

Place, publisher, year, edition, pages
CEUR-WS , 2023. article id 9284
Series
CEUR Workshop Proceedings, ISSN 1613-0073 ; 3485
Keywords [en]
Knowledge Representation, Ontology-based Data Access, View Updates, Virtual Knowledge Graph (VKG)
National Category
Computer Sciences Computer Systems
Identifiers
URN: urn:nbn:se:umu:diva-215832Scopus ID: 2-s2.0-85174215075OAI: oai:DiVA.org:umu-215832DiVA, id: diva2:1809839
Conference
17th International Rule Challenge and 7th Doctoral Consortium @ RuleM+RR, RuleML+RR-Companion 2023, Oslo, September 18-20, 2023
Funder
Wallenberg AI, Autonomous Systems and Software Program (WASP)Available from: 2023-11-06 Created: 2023-11-06 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 EsdrasŠimkus, MantasCalvanese, Diego

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