Publication details

An INSPIRE-based vocabulary for the publication of Agricultural Linked Data

Authors

PALMA Raúl ŘEZNÍK Tomáš ESBRÍ Miguel CHARVÁT Karel MAZUREK Cezary

Year of publication 2016
Type Article in Proceedings
Conference Ontology Engineering (Lecture Notes in Computer Science)
MU Faculty or unit

Faculty of Science

Citation
Doi http://dx.doi.org/10.1007/978-3-319-33245-1_13
Field Earth magnetism, geography
Keywords linked data; semantics; agriculture; INSPIRE; OWL
Description FOODIE project aims at building an open and interoperable agricultural specialized platform on the cloud for the management, discovery and largescale integration of data relevant for farming production. In particular, the integration focuses on existing open datasets as well as their publication in Linked data format in order to maximize their reusability and enable the exploitation of the extra knowledge derived from the generated links. Based on such data, for instance, FOODIE platform aims at providing high-value applications and services supporting the planning and decision-making processes of different stakeholders related to the agricultural domain. The keystone for data integration is FOODIE data model, which has been defined by reusing and extending current standards and best practices, including data specifications from the INSPIRE directive which are in turn based on the ISO/OGC standards for geographical information. However, as these data specifications are available as XML documents, the first step to publish Linked Data required transforming or lifting FOODIE data model into semantic format. In this paper, we describe this process, which was conducted semi-automatically by reusing existing tools, and adhering to the mapping rules for transforming geographic information UML models to OWL ontologies defined by the ISO 19150-2 standard. We describe the challenges associated to this transformation, and finally, we describe the generated ontology, providing an INSPIRE-based vocabulary for the publication of Agricultural Linked Data.
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