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Authors: Valéria M. Pequeno 1 ; Vânia M. P. Vidal 2 and Tiago Vinuto 2

Affiliations: 1 Universidade Autonoma de Lisboa Luís de Camões and INESC-ID, Portugal ; 2 Universidade Federal do Ceará, Brazil

Keyword(s): Mapping Patterns, RDF-to-RDF Mapping, R2R Mapping, Mapping Assertion, RDF Model, Ontologies.

Related Ontology Subjects/Areas/Topics: Cloud Computing ; Coupling and Integrating Heterogeneous Data Sources ; Databases and Information Systems Integration ; Enterprise Information Systems ; Non-Relational Databases ; Semantic Web Technologies ; Services Science ; Software Agents and Internet Computing

Abstract: Translating data from linked data sources to the vocabulary that is expected by a linked data application requires a large number of mappings and can require a lot of structural transformations as well as complex property value transformations. The R2R mapping language is a language based on SPARQL for publishing expressive mappings on the web. However, the specification of R2R mappings is not an easy task. This paper therefore proposes the use of mapping patterns to semi-automatically generate R2R mappings between RDF vocabularies. In this paper, we first specify a mapping language with a high level of abstraction to transform data from a source ontology to a target ontology vocabulary. Second, we introduce the proposed mapping patterns. Finally, we present a method to semi-automatically generate R2R mappings using the mapping patterns.

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Paper citation in several formats:
Pequeno, V.; Vidal, V. and Vinuto, T. (2018). Towards Semi-automatic Generation of R2R Mappings. In Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-298-1; ISSN 2184-4992, SciTePress, pages 237-244. DOI: 10.5220/0006801602370244

@conference{iceis18,
author={Valéria M. Pequeno. and Vânia M. P. Vidal. and Tiago Vinuto.},
title={Towards Semi-automatic Generation of R2R Mappings},
booktitle={Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2018},
pages={237-244},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006801602370244},
isbn={978-989-758-298-1},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Towards Semi-automatic Generation of R2R Mappings
SN - 978-989-758-298-1
IS - 2184-4992
AU - Pequeno, V.
AU - Vidal, V.
AU - Vinuto, T.
PY - 2018
SP - 237
EP - 244
DO - 10.5220/0006801602370244
PB - SciTePress