We present a semantic technology-based approach to emerging environmental information systems. We used our linked data approach in the Tetherless World Constellation Semantic Water Quality Portal (TWC-SWQP). Our integration scheme uses a core domain ontology and integrates water data from different authoritative sources along with multiple regulation ontologies to enable pollution detection and monitoring. An OWL-based reasoning scheme identifies pollution events relative to user chosen regulations. Our approach also captures and leverages provenance to improve transparency. In addition, semantic water quality portal features provenance-based facet generation, query answering and data validation over the integrated data via SPARQL. We introduce the approach and the water portal, and highlight some of its potential impacts for the future of environmental monitoring systems.
Publication: Zheng, J.,iWang, P., Patton, E., Lebo, T., Luciano, J., and McGuinness, D. (2011). "A Semantically-Enabled Provenance-Aware Water Quality Portal." (PDF)
Semantic Water Quality Portal static demo (PDF):
https://tw.rpi.edu/media/286 (Part1)
https://tw.rpi.edu/media/287 (Part 2)
Semantic Water Quality Portal Use Case document (DOC):
https://tw.rpi.edu/media/285
https://tw.rpi.edu/media/286 (Part1)
https://tw.rpi.edu/media/287 (Part 2)
Semantic Water Quality Portal Use Case document (DOC):
https://tw.rpi.edu/media/285
Google Code repository:
https://code.google.com/archive/p/swqp/
https://code.google.com/archive/p/swqp/
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