Putting Semantic Technology into Practice: Expanding the SemantEco Environment to Support Natural Resource Managers

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Abstract:

We aim to provide a broad and deep range of decision support tools for resource managers who need to examine large complex ecosystems and make recommendations in the face of many tradeoffs and conflicting drivers. We take a semantic technology approach, leveraging background ontologies and the growing body of open linked data. In previous work, we designed and implemented a semantically-enabled environmental monitoring framework called SemantEco and used it to build a water quality portal named SemantAqua. In this work, we significantly extend SemantEco to include knowledge required to support resource decisions concerning endangered species and their habitats. Our previous system included foundational ontologies to support environmental regulation violations, and relevant human health effects. Our enhanced framework includes foundational ontologies to support modeling of wildlife observation and wildlife health impacts, thereby enabling deeper and broader support for large ecosystem analysis in the face of environmental pollution. Our results include a refactored and expanded version of the SemantEco portal. Additionally the updated system is now compatible with the emerging best in class Extensible Observation Ontology (OBOE). A wider range of relevant data has been integrated, focusing on additions concerning wildlife health. The resulting system stores and exposes provenance concerning where the data came from, how it was used, and also the rationale for choosing the data. In this paper, we describe the system, highlight its research contributions, and describe current and envisioned usage.

History

DateCreated ByLink
July 24, 2012
00:41:24
Ping WangDownload
June 26, 2012
14:06:52
Ping WangDownload
June 26, 2012
14:00:04
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:

Knowledge Provenance
Lead Professor: Deborah L. McGuinness
Description: Knowledge Provenance
Concepts: Provenance, Semantic Web
Semantic eScience
Lead Professor: Peter Fox
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
Lead Professor: Jim Hendler, Deborah L. McGuinness
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