The RML Ontology: A Community-Driven Modular Redesign After a Decade of Experience in Mapping Heterogeneous Data to RDF

dc.contributor.affiliationUniversidade de Santiago de Compostela. Departamento de Electrónica e Computación
dc.contributor.authorIglesias-Molina, Ana
dc.contributor.authorVan Assche, Dylan
dc.contributor.authorArenas-Guerrero, Julián
dc.contributor.authorDe Meester, Ben
dc.contributor.authorDebruyne, Christophe
dc.contributor.authorJozashoori, Samaneh
dc.contributor.authorMaria, Pano
dc.contributor.authorMichel, Franck
dc.contributor.authorChaves Fraga, David
dc.contributor.authorDimou, Anastasia
dc.date.accessioned2025-03-19T09:10:17Z
dc.date.available2025-03-19T09:10:17Z
dc.date.issued2023-10-27
dc.description.abstractThe Relational to RDF Mapping Language (R2RML) became a W3C Recommendation a decade ago. Despite its wide adoption, its potential applicability beyond relational databases was swiftly explored. As a result, several extensions and new mapping languages were proposed to tackle the limitations that surfaced as R2RML was applied in real-world use cases. Over the years, one of these languages, the RDF Mapping Language (RML), has gathered a large community of contributors, users, and compliant tools. So far, there has been no well-defined set of features for the mapping language, nor was there a consensus-marking ontology. Consequently, it has become challenging for non-experts to fully comprehend and utilize the full range of the language’s capabilities. After three years of work, the W3C Community Group on Knowledge Graph Construction proposes a new specification for RML. This paper presents the new modular RML ontology and the accompanying SHACL shapes that complement the specification. We discuss the motivations and challenges that emerged when extending R2RML, the methodology we followed to design the new ontology while ensuring its backward compatibility with R2RML, and the novel features which increase its expressiveness. The new ontology consolidates the potential of RML, empowers practitioners to define mapping rules for constructing RDF graphs that were previously unattainable, and allows developers to implement systems in adherence with [R2]RML.
dc.description.sponsorshipAna Iglesias-Molina is supported by the project Knowledge Spaces (Grant PID2020-118274RB-I00 funded by MCIN/AEI/10.13039/501100011033). Dylan Van Assche is supported by the Special Research Fund of Ghent University under grant BOF20/DOC/132. Ben de Meester is supported by SolidLab Vlaanderen (Flemish Government, EWI and RRF project VV023/10). Julián Arenas-Guerrero is partially supported by the Euratom Research and Training Programme 2019–2020 under grant agreement No 900018 (ENTENTE project). David Chaves-Fraga is partially supported by the Galician Ministry of Culture, Education, Professional Training, and University, by the European Regional Development Fund (ERDF/FEDER program) through grant ED431C2022/19 and by the Madrid Government (Comunidad de Madrid-Spain) under the Multiannual Agreement with Universidad Politécnica de Madrid in the line Support for R &D projects for Beatriz Galindo researchers, in the context of the V PRICIT (Regional Programme of Research and Technological Innovation). Anastasia Dimou is partially supported by Flanders Make, the strategic research centre for the manufacturing industry and the Flanders innovation and entrepreneurship (VLAIO) via the KG3D project. The collaboration of Dylan Van Assche, Ben De Meester, Christophe Debruyne, David Chaves-Fraga and Anastasia Dimou is stimulated by the KG4DI FWO scientific research network (W001222N).
dc.identifier.citationIglesias-Molina, A. et al. (2023). The RML Ontology: A Community-Driven Modular Redesign After a Decade of Experience in Mapping Heterogeneous Data to RDF. In: Payne, T.R., et al. The Semantic Web – ISWC 2023. ISWC 2023. Lecture Notes in Computer Science, vol 14266. Springer, Cham. https://doi.org/10.1007/978-3-031-47243-5_9
dc.identifier.doi10.1007/978-3-031-47243-5_9
dc.identifier.isbn978-3-031-47242-8
dc.identifier.isbn978-3-031-47243-5
dc.identifier.urihttps://hdl.handle.net/10347/40338
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofseriesLecture Notes in Computer Science; 14266
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-118274RB-I00
dc.relation.publisherversionhttps://doi.org/10.1007/978-3-031-47243-5_9
dc.rights⃝The Author(s) 2023. Attribution 4.0 International
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectDeclarative Language
dc.subjectR2RML
dc.subjectRML
dc.subjectKnowledge Graph
dc.titleThe RML Ontology: A Community-Driven Modular Redesign After a Decade of Experience in Mapping Heterogeneous Data to RDF
dc.typebook part
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dspace.entity.typePublication
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relation.isAuthorOfPublication.latestForDiscoveryff664f8c-843d-44f0-bb5c-fe605fe90289

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