The time dimension in conceptual modelling
Information Systems
Maintaining knowledge about temporal intervals
Communications of the ACM
Toward the semantic geospatial web
Proceedings of the 10th ACM international symposium on Advances in geographic information systems
The description logic handbook
An ontology of time for the semantic web
ACM Transactions on Asian Language Information Processing (TALIP) - Special Issue on Temporal Information Processing
Literature review of spatio-temporal database models
The Knowledge Engineering Review
A Reusable Ontology for Fluents in OWL
Proceedings of the 2006 conference on Formal Ontology in Information Systems: Proceedings of the Fourth International Conference (FOIS 2006)
Use of geospatial analyses for semantic reasoning
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part I
SOWL: a framework for handling spatio-temporal information in OWL 2.0
RuleML'2011 Proceedings of the 5th international conference on Rule-based reasoning, programming, and applications
ESWC'10 Proceedings of the 7th international conference on The Semantic Web: research and Applications - Volume Part I
Modeling consistency of spatio-temporal graphs
Data & Knowledge Engineering
| Hi-index | 0.00 |
This work introduces an ontology-based spatio-temporal data model to represent entities evolving in space and time. A dynamic phenomenon generates a complex relationship network between the entities involved in the process. At the abstract level, the relationships can be identity or topological filiations. The existence of an identity filiation depends on whether the object changes its identity or not. On the other hand, topological filiations are based exclusively on the spatial component, like in the case of growth, reduction, merging or splitting. When combining identity and topological filiations, six filiation relationships are obtained, forming a second abstract level. Upper-level filiation relationships provide better semantic vocabulary to describe the modeled phenomena, thus allowing the implementation of spatial, temporal and identity constraints. In this paper, we present a method based on identity and topological filiation relationships, to improve the capabilities of standard knowledge bases using Semantic Web technologies. Our method enables us to check the consistency of spatio-temporal and semantic data. An example is given in the field of urban growth to show the capabilities of the model.