A Semantically-Enabled Provenance-Aware Water Quality Portal (under review)

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Abstract:

Environmental informatics applications often analyze data collected from various sources. Both data collection and data analysis benefit from expert knowledge. However, if applications are to be used by a broader range of users with less expert knowledge, applications will need to include a deeper understanding of the data used and analysis performed. We present the Tetherless World Constellation Semantic Water Quality Portal as both a water quality portal application and as an example of a semantic approach to environmental informatics applications. The portal integrates water data from multiple sources and captures the semantics of the data in a simple water quality ontology. Portal users can identify polluted water sources and polluting facilities according to multiple regulation perspectives and geographic constraints by using visualizations of semantically-enabled queries. Further, knowledge provenance is encoded in the data capture and integration services to enable provenance-based queries and reasoning capability.

History

DateCreated ByLink
July 14, 2011
00:17:30
Ping WangDownload
July 14, 2011
00:02:43
Ping WangDownload

Related Projects:

SemantAQUA LogoSemantic Water Quality Portal (SemantAQUA)
Principal Investigator: Deborah L. McGuinness
Co Investigator: Joanne S. Luciano
Description: 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.

Related Research Areas:

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Lead Professor: Deborah L. McGuinness
Description: Inference And Trust
Concepts: Semantic Web
Knowledge Provenance
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Description: Knowledge Provenance
Concepts: , Semantic Web
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Description:
Science has fully entered a new mode of operation. E-science, defined as a combination of science, informatics, computer science, cyberinfrastructure and information technology is changing the way all of these disciplines do both their individual and collaborative work.
As semantic technologies have been gaining momentum in various e-Science areas (for example, W3C's new interest group for semantic web health care and life science), it is important to offer semantic-based methodologies, tools, middleware to facilitate scientific knowledge modeling, logical-based hypothesis checking, semantic data integration and application composition, integrated knowledge discovery and data analyzing for different e-Science applications.
Partially influenced by the Artificial Intelligence community, the Semantic Web researchers have largely focused on formal aspects of semantic representation languages or general-purpose semantic application development, with inadequate consideration of requirements from specific science areas. On the other hand, general science researchers are growing ever more dependent on the web, but they have no coherent agenda for exploring the emerging trends on the semantic web technologies. It urgently requires the development of a multi-disciplinary field to foster the growth and development of e-Science applications based on the semantic technologies and related knowledge-based approaches.

Concepts: eScience
Web Science
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Description: Web Science is the study of the World Wide Web and its impact on both society and technology, positioning the Web as an object of scientific study unto itself. Web Science recognizes the Web as a transformational, disruptive technology; its practitioners study the Web, its components, facets and characteristics. Ultimately, Web Science is about understanding the Web and anticipating how it might evolve in the future.
Concepts: Semantic Web