The World Wide Web has provided the ability to share documents in a large community, and then, it became necessary to represent such information in a way comprehensible not only by humans but also by software agents: this is the move from the Web of Documents to the Web of Data. The Semantic Web refers to the scientiﬁc eﬀort initiated by researchers in Artiﬁcial Intelligence and standardized by the W3C consortium, in order to attach semantics to resources available on the Web (documents and data). This involves categorizing, indexing and linking them and formally expressing the knowledge that will allow software agents to extract, combine and eventually deduce information from published datasets. Ontologies as formal and explicit speciﬁcations of a shared conceptualization about a more or less speciﬁc domain of application are one of the building blocks of the Semantic Web.
Research in STeamer explores the ability of logical and structured formalisms and associated reasoners that are supporting ontologies and the Semantic Web to cope with both representation and reasoning dedicated to spatial and temporal information. Our objective is two-fold: we investigate the use of diﬀerent standard languages for ontologies (OWL, RDFS, . . . ) for handling (i.e. representing, identifying, inferring, querying…) complex spatial and temporal relations, while pushing the limits of existing standard ontologies or vocabularies about time (for instance OWL-Time) and about space (for instance GeoRSS) including associated reasoners and query languages (SPARQL, GeoSPARQL). Along with the study of how to implement in the Semantic Web technology stack the proposition of the A. D. Miron’s PhD thesis about the detection of semantic associations in spatiotemporal ontologies, we have worked on the way to eﬃciently build ontologies using an Aristotelian modelling approach based on a subset of OWL. A ongoing research master thesis explore how this approach can be used to deﬁne an ontology of geographic features from the tags in OpenStreetMap.