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Arenas-Guerrero, JulianCorresponding AuthorIglesias-Molina, AnaAuthorChaves-Fraga, DavidAuthorGarijo, DanielAuthorCorcho, OscarAuthor

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May 13, 2025
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Article

Declarative generation of RDF-star graphs from heterogeneous data

Publicated to: Semantic Web. 16 (2): SW243602- - 2025-01-01 16(2), DOI: 10.3233/sw-243602

Authors:

Arenas-Guerrero, J; Iglesias-Molina, A; Chaves-Fraga, D; Garijo, D; Corcho, O; Dimou, A
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Affiliations

Flanders Make, DTAI FET, Leuven, Belgium - Author
Katholieke Univ Leuven, Declarat Languages & Artificial Intelligence Grp, Leuven, Belgium - Author
Univ Politecn Madrid, Ontol Engn Grp, Madrid, Spain - Author
Univ Santiago De Compostela, Grp Sistemas Intelixentes, Santiago De Compostela, Spain - Author
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Abstract

RDF-star has been proposed as an extension of RDF to make statements about statements. Libraries and graph stores have started adopting RDF-star, but the generation of RDF-star data remains largely unexplored. To allow generating RDF-star from heterogeneous data, RML-star was proposed as an extension of RML. However, no system has been developed so far that implements the RML-star specification. In this work, we present Morph-KGC(star), which extends the Morph-KGC materialization engine to generate RDF-star datasets. We validate Morph-KGC(star) by running test cases derived from the N-Triples-star syntax tests and we apply it to two real-world use cases from the biomedical and open science domains. We compare the performance of our approach against other RDF-star generation methods (SPARQL-Anything), showing that Morph-KGC(star) scales better for large input datasets, but it is slower when processing multiple smaller files.
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Keywords

Data integratioData integrationKnowledge graphsRdf-starRml-star

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Semantic Web due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2025, it was in position 44/147, thus managing to position itself as a Q2 (Segundo Cuartil), in the category Computer Science, Theory & Methods. Notably, the journal is positioned en el Cuartil Q2 para la agencia Scopus (SJR) en la categoría .

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2025-12-20:

  • Open Alex: 5
  • Google Scholar: 5
  • Scopus: 1
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Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-12-20:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 4.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 7 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 1.
  • The number of mentions on the social network X (formerly Twitter): 1 (Altmetric).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.
  • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: https://oa.upm.es/88073/

As a result of the publication of the work in the institutional repository, statistical usage data has been obtained that reflects its impact. In terms of dissemination, we can state that, as of

  • Views: 143
  • Downloads: 41
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Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: Belgium.

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (ARENAS GUERRERO, JULIAN) .

the author responsible for correspondence tasks has been ARENAS GUERRERO, JULIAN.

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Awards linked to the item

This work was partially funded by the project "Knowledge Spaces: Tecnicas y herramientas para la gestion de grafos de conocimientos para dar soporte a espacios de datos" (Grant PID2020-118274RB-I00, funded by MCIN/AEI/10.13039/501100011033) and by the Euratom Research and Training Programme 2019-2020 ENTENTE under Grant 900018. The work also received partial financial support from the Galician Ministry of Education, University and Professional Training, and the European Regional Development Fund (ERDF/FEDER program) through grants ED431C2018/29 and ED431G2019/04. Daniel Garijo is supported by the Madrid Government (Comunidad de Madrid - Spain) under the Multiannual Agreement with Universidad Politecnica de Madrid in the line Support for R&D projects for Beatriz Galindo researchers, in the context of the VPRICIT, and through the call Research Grants for Young Investigators from Universidad Politecnica de Madrid. Anastasia Dimou and David Chaves-Fraga are also supported by Flanders Make.
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