Geospatial Semantic Web Interoperability Experiment

Initial Plan

This Interoperability Experiment (IE) will address several important steps towards the development of a Geospatial Semantic Web (GSW), where discovery, query, and consumption of geospatial content are based on formal semantic specification. Many pieces of the GSW puzzle have been worked extensively in the last several years; this experiment aims to augment WFS/FE with a semantic query capability, through the definition of an ontology for the geospatial intelligence community. It will be necessary to work out a distributed architecture in which implement an end-to-end geospatial query use case. Some of the most significant elements of this architecture include:

  • Development / encoding of formal geospatial ontologies,
  • WFS/FE interfaces which can provide service information formulated in the OWL-S semantic expression language referencing those ontologies,
  • WFS/FE service interfaces which can accept query requests in a semantic query language,
  • Tools for easily generating semantically expressed geospatial information
  • Implemented distributed components for use in processing geospatial queries

While several deliverables are described for this Interoperability Experiment, the most important deliverable shall be the demonstration of an end-to-end semantic geospatial query itself, where WFS/FE services relevant to the query are discovered through knowledgebase reasoning from a collection of interoperable components provided by the experiment participants.


DocumentVersionOGC Document NumberEditorDate Published
Geospatial Semantic Web Interoperabiltiy Experiment Report  0.5.0  06-002r1  Joshua Lieberman  2006-08-21
The Semantic Web seeks to make the meaning as accessible as the material, by enabling connections - which are both logical and (machine) actionable - between concepts which a user presently understands and those which may be new and foreign. The Geospatial Semantic Web extends this capability to both content and concepts that are specifically spatial, temporal, and geographic in nature, giving both people and machines true access to a wider range of knowledge.