SemantEco: a semantically powered modular architecture for integrating distributed environmental and ecological data
Future Generation Computer Systems
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Abstract
We aim to inform the development 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 linked open 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. Our previous system included foundational ontologies to support environmental regulation violations and relevant human health effects. In this work, we discuss SemantEco’s new architecture that supports modular extensions and makes it easier to support additional domains. Our enhanced framework includes foundational ontologies to support modeling of wildlife observation and wildlife health impacts, thereby enabling deeper and broader support for more holistically examining the effects of environmental pollution on ecosystems. We conclude with a discussion of how, through the application of semantic technologies, modular designs will make it easier for resource managers to bring in new sources of data to support more complex use cases.
Suggested Citation
Patton, E.W., Seyed, P., Wang, P., Fu, L., Dein, F.J., Bristol, R., McGuinness, D.L., 2014, SemantEco: a semantically powered modular architecture for integrating distributed environmental and ecological data: Future Generation Computer Systems, v. 36, p. 430-440, https://doi.org/10.1016/j.future.2013.09.017.
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | SemantEco: a semantically powered modular architecture for integrating distributed environmental and ecological data |
| Series title | Future Generation Computer Systems |
| DOI | 10.1016/j.future.2013.09.017 |
| Volume | 36 |
| Year Published | 2014 |
| Language | English |
| Publisher | Elsevier |
| Contributing office(s) | National Wildlife Health Center, Core Science Analytics, Synthesis, and Libraries |
| Description | 11 p. |
| Larger Work Type | Article |
| Larger Work Subtype | Journal Article |
| Larger Work Title | Future Generation Computer Systems |
| First page | 430 |
| Last page | 440 |