April 28, 2024
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Article

An ontological approach for representing declarative mapping languages

Publicated to: Semantic Web. 15 (1): 191-221 - 2024-01-01 15(1), DOI: 10.3233/SW-223224

Authors:

Iglesias-Molina, A; Cimmino, A; Ruckhaus, E; Chaves-Fraga, D; García-Castro, R; Corcho, O
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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
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Abstract

Knowledge Graphs are currently created using an assortment of techniques and tools: ad hoc code in a programming language, database export scripts, OpenRefine transformations, mapping languages, etc. Focusing on the latter, the wide variety of use cases, data peculiarities, and potential uses has had a substantial impact in how mappings have been created, extended, and applied. As a result, a large number of languages and their associated tools have been created. In this paper, we present the Conceptual Mapping ontology, that is designed to represent the features and characteristics of existing declarative mapping languages to construct Knowledge Graphs. This ontology is built upon the requirements extracted from experts experience, a thorough analysis of the features and capabilities of current mapping languages presented as a comparative framework; and the languages' limitations discussed by the community and denoted as Mapping Challenges. The ontology is evaluated to ensure that it meets these requirements and has no inconsistencies, pitfalls or modelling errors, and is publicly available online along with its documentation and related resources.
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Keywords

Knowledge graphKnowledge graphsMapping languagesOntology descriptionR2rmlRdSparql-to-sql

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, 2024 there are still no calculated indicators, but in 2023, 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 Computer Networks and Communications.

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 2026-04-27:

  • Google Scholar: 8
  • WoS: 4
  • Scopus: 7
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Impact and social visibility

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/90400/

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: 104
  • Downloads: 21
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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 (IGLESIAS MOLINA, ANA) and Last Author (CORCHO GARCIA, OSCAR).

the author responsible for correspondence tasks has been IGLESIAS MOLINA, ANA.

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Awards linked to the item

We are thankful for the feedback provided by Anastasia Dimou during the elaboration of this paper. The work presented in this paper is supported by the Spanish Ministerio de Ciencia e Innovacion funds under the Spanish I + D + I national project KnowledgeSpaces: Tecnicas y herramientas para la gestion de grafos de conocimientos para dar soporte a espacios de datos (PID2020-118274RB-I). Also, this work is partially funded by the EuropeanUnion's Horizon 2020 Research and Innovation Programme through the AURORAL project, Grant Agreement No. 101016854. David Chaves-Fraga is supported by the Spanish Minister of Universities
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