Sirene is the official database of French enterprises (legal units) and establishments (local units). In response to the SemStats 2019 Call for Challenge to model and provision the Sirene data as RDF, we propose the use of the euBusinessGraph ontology as a basis for modeling and publishing Sirene data as Linked Data. In this paper we discuss the suitability of the euBusinessGraph ontology to cover key Sirene entities, present extensions to the euBusinessGraph ontology developed to accommodate the modelling needs of the Sirene key entities. Furthermore, we describe the Linked Data publication process, covering the needed Sirene data transformations and RDFization, as well as the technology stack supporting the process. The result is key entities data from Sirene published as Linked Data, together with a reproducible process for generation of Linked Data from Sirene data.

El Kader, S., Nikolov, N., von Zernichow, B., Cutrona, V., Palmonari, M., Elvesaeter, B., et al. (2019). Modeling and publishing French business register (SIRENE) data as linked data using the EubusinessGraph ontology. Intervento presentato a: 2019 Joint International Workshops on Sensors and Actuators on the Web, and Semantic Statistics, SAWSemStats 2019, Auckland; New Zealand.

Modeling and publishing French business register (SIRENE) data as linked data using the EubusinessGraph ontology

Cutrona V.;Palmonari M.;
2019

Abstract

Sirene is the official database of French enterprises (legal units) and establishments (local units). In response to the SemStats 2019 Call for Challenge to model and provision the Sirene data as RDF, we propose the use of the euBusinessGraph ontology as a basis for modeling and publishing Sirene data as Linked Data. In this paper we discuss the suitability of the euBusinessGraph ontology to cover key Sirene entities, present extensions to the euBusinessGraph ontology developed to accommodate the modelling needs of the Sirene key entities. Furthermore, we describe the Linked Data publication process, covering the needed Sirene data transformations and RDFization, as well as the technology stack supporting the process. The result is key entities data from Sirene published as Linked Data, together with a reproducible process for generation of Linked Data from Sirene data.
paper
EuBusinessGraph; Linked Data; Sirene
English
2019 Joint International Workshops on Sensors and Actuators on the Web, and Semantic Statistics, SAWSemStats 2019
2019
2019
2549
none
El Kader, S., Nikolov, N., von Zernichow, B., Cutrona, V., Palmonari, M., Elvesaeter, B., et al. (2019). Modeling and publishing French business register (SIRENE) data as linked data using the EubusinessGraph ontology. Intervento presentato a: 2019 Joint International Workshops on Sensors and Actuators on the Web, and Semantic Statistics, SAWSemStats 2019, Auckland; New Zealand.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/293720
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