HuTO: an Human Time Ontology for Semantic Web Applications
This work addresses the need for formal temporal representation in heterogeneous data for software agents in the Semantic Web domain, though it appears incremental as it builds on existing ontology concepts.
The authors tackled the problem of representing and querying temporal data in Semantic Web applications by introducing HuTO, an RDFS ontology that models non-convex intervals and includes normalization and reasoning rules, enabling more effective information retrieval with temporal dimensions.
The temporal phenomena have many facets that are studied by different communities. In Semantic Web, large heterogeneous data are handled and produced. These data often have informal, semi-formal or formal temporal information which must be interpreted by software agents. In this paper we present Human Time Ontology (HuTO) an RDFS ontology to annotate and represent temporal data. A major contribution of HuTO is the modeling of non-convex intervals giving the ability to write queries for this kind of interval. HuTO also incorporates normalization and reasoning rules to explicit certain information. HuTO also proposes an approach which associates a temporal dimension to the knowledge base content. This facilitates information retrieval by considering or not the temporal aspect.