Welcome to the Semantic Enablement Community
Welcome to the Semantic Enablement Community home. You will find all information about on-going developments on developing a Semantic Enablement Layer (SEL) for Spatial Data Infrastructures (SDI).
Semantic Enablement Community
This community focuses on providing a semantic enablement layer for services developed within the 52°North communities to support semantics-based information retrieval, discovery and querying, on-the-fly integration, semantic translation, as well as further reasoning services.
Vision and Mission
Our mission is to investigate the need for semantics and geo-ontologies in 52°North, as well as to provide a Semantic Enablement (SE) layer for the services developed by other 52°North communities. This layer will consist of two tiers of ontologies. The first tier will specify a set of ontologies per kind of service (e.g., Sensor Observation Services or Web Processing Services) which define the basic vocabulary such as Sensor, Event, or Observation and will be based on OGC specifications and top-level ontologies (such as DOLCE and BFO). The second ontological tier will provide types and relations for specific services such as a weather observation service. In addition to providing ontologies, the semantics community will also implement interfaces and add-ons to existing services to support semantics-based information retrieval, discovery, on-the-fly integration, semantic translation, and other reasoning services. Examples include services for the discovery of appropriate sensors to solve a given task, and a similarity search extension to catalog services for use with Web Feature Services. The semantics community will also focus on the integration of additional contextual information to enable context-aware discovery.
The long-term vision is to combine the top-down view of ontological research with a data (and therefore sensor) driven bottom-up approach to support complex queries. For instance, instead of searching sensors, deciding about temporal and spatial resolution, location, and further settings to track a particular phenomenon by hand, it should be possible to select the phenomenon (such as the spread of diseases) from an ontology and let the reasoner discover, select and configure the necessary sensors semi-automatically.