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Using Ontologies to Relate Resource Management Actions to Environmental Monitoring Data in South East Queensland

Using Ontologies to Relate Resource Management Actions to Environmental Monitoring Data in South East Queensland

Jane Hunter, Peter Becker, Abdulmonem Alabri, Catharine van Ingen, Eva Abal
Copyright: © 2011 |Volume: 2 |Issue: 1 |Pages: 19
ISSN: 1947-3192|EISSN: 1947-3206|EISBN13: 9781613505472|DOI: 10.4018/jaeis.2011010101
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MLA

Hunter, Jane, et al. "Using Ontologies to Relate Resource Management Actions to Environmental Monitoring Data in South East Queensland." IJAEIS vol.2, no.1 2011: pp.1-19. http://doi.org/10.4018/jaeis.2011010101

APA

Hunter, J., Becker, P., Alabri, A., van Ingen, C., & Abal, E. (2011). Using Ontologies to Relate Resource Management Actions to Environmental Monitoring Data in South East Queensland. International Journal of Agricultural and Environmental Information Systems (IJAEIS), 2(1), 1-19. http://doi.org/10.4018/jaeis.2011010101

Chicago

Hunter, Jane, et al. "Using Ontologies to Relate Resource Management Actions to Environmental Monitoring Data in South East Queensland," International Journal of Agricultural and Environmental Information Systems (IJAEIS) 2, no.1: 1-19. http://doi.org/10.4018/jaeis.2011010101

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Abstract

The Health-e-Waterways Project is a multi-disciplinary collaboration between the University of Queensland, Microsoft Research and the South East Queensland Healthy Waterways Partnership (SEQ-HWP). This project develops the underlying technological framework and set of services to enable streamlined access to the expanding collection of real-time, near-real-time and static datasets related to water resource management in South East Queensland. More specifically, the system enables water resource managers to access the datasets being captured by the various agencies participating in the SEQ HWP Ecosystem Health Monitoring Program (EHMP). It also provides online access to the statistical data processing tools that enable users to analyse the data and generate online ecosystem report cards dynamically via a Web mapping interface. The authors examine the development of ontologies and semantic querying tools to integrate disparate datasets and relate management actions to water quality indicators for specific regions and periods. This semantic data integration approach enables scientists and resource managers to identify which actions are having an impact on which parameters and adapt the management strategies accordingly. This paper provides an overview of the semantic technologies developed to underpin the adaptive management framework that is the central philosophy behind the SEQ HWP.

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