Reference : Spatio-temporal reasoning in CIDOC CRM: an hybrid ontology with GeoSPARQL and OWL-Time
Scientific congresses and symposiums : Paper published in a journal
Engineering, computing & technology : Computer science
http://hdl.handle.net/2268/228461
Spatio-temporal reasoning in CIDOC CRM: an hybrid ontology with GeoSPARQL and OWL-Time
English
Nys, Gilles-Antoine mailto [Université de Liège - ULiège > Département de géographie > Unité de Géomatique - Topographie et géométrologie >]
Van Ruymbeke, Muriel mailto [Université de Liège - ULiège > Département de géographie > Unité de Géomatique - Topographie et géométrologie >]
Billen, Roland mailto [Université de Liège - ULiège > Département de géographie > Unité de Géomatique - Topographie et géométrologie >]
13-Oct-2018
CEUR Workshop Proceedings
RWTH Aachen University
2230
COARCH 2018 - Computing Techniques For Spatio-Temporal Data in Archaeology And Cultural Heritage
Yes
International
1613-0073
Aachen
Germany
2nd Workshop On Computing Techniques For Spatio-Temporal Data in Archaeology And Cultural Heritage
28-08-2018
Computer Science Department, University of Verona
Geomatics Unit, ULiège
Melbourne
Australia
[en] CIDOC CRM ; hybrid ontologies ; cultural heritage ; spatio-temporal reasoning
[en] Semantic description of cultural heritage information is already widely structured through CIDOC
CRM and its different extensions. This shared understanding of cultural heritage information
has already proved its usefulness. Until now, despite its spatial and temporal data management
proposition, lack standardization limited the possibilities in terms of reasoning and workability.
This paper proposes to increase the potentiality offered by the current scheme by including
GeoSPARQL and OWL-Time in the framework. The result, as hybrid ontology, allows concurrent
spatial and temporal handling. These are used to provide a near-full data management for
complex spatio-temporal reasoning and querying through SPARQL queries. Example queries
depicting the strength of the approach and allowing knowledge discovery in huge archaeological
datasets illustrate its benefits
http://hdl.handle.net/2268/228461
http://ceur-ws.org/Vol-2230/paper_04.pdf

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