Semantic Data Cube

The Semantic Data Cube enables the semantic enrichment of the Earth System Data Cube (ESDC). The Semantic Data Cube will allow users to query Earth Observation data, other Linked Open Data, and information/knowledge extracted from the data using a semantic query language, thus creating new value chains.

The core of the Semantic Data Cube is Ontop-spatial. Ontop-spatial creates virtual geospatial Resource Description Framework graphs – commonly known as RDF graphs – on top of geospatial data models, such as the ones supported by ESDC. The geometries are then mapped to GeoSPARQL geometry literals using ontologies and R2RML/OBDA mappings. Ontop-spatial can be used as a standard SPARQL endpoint that can execute GeoSPARQL queries on top of ESDC. Therefore, it can be used in complement with other tools that produce, manage, explore, and visualize geospatial RDF data.

The new semantic data cube technology we will develop, will allow us to express the following classes of queries:

  1. Queries on the Earth Observation data.
  2. Semantic queries on the low-level content of the image.
  3. Semantic queries on the high-level content of the image.
  4. Any of the above query classes together with a spatial and temporal extent.
  5. Any of the above query classes together with a reference to an external data source.

In current data cubes, only queries of Class 1 and 2 are possible. In the Semantic Data Cubes to be implemented in DeepCube, all of the above classes of queries will be possible. This will be a significant research output of the project and will assist in the implementation of three Use Cases: climate induced migration in Africa, fire hazard forecasting in the Mediterranean, and Copernicus services for sustainable tourism.

The Semantic Data Cube, will be the first international approach in this technology and will be implemented by extending the geospatial ontology-based data access system Ontop-spatial. The new system will allow users to query Earth Observation data and information/knowledge extracted from the data, using a semantic query language. This query will be rewritten using ontology axioms and mappings, and will be executed at the data sources (data cubes and other external data sources). The answers will be collected and will be returned to the user.

Interested in learning more? Contact us!
Manolis Koubarakis,
Dimitris Bilidas,