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

Hunter, Jane; Becker, Peter; Alabri, A.; Ingen, Catharine van; Abal, Eva

doi:10.4018/jaeis.2011010101

Cited by 11 publications

(11 citation statements)

References 12 publications

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“…[50] S33 Towards semantically-enabled exploration and analysis of environmental ecosystems [51] S34 Using ontologies to relate resource management actions to environmental monitoring data in South East Queensland [52] Given the research question RQ5, the thirty-four-study group was classified by the type of research developed, using the definition of Petersen et al [14]. The classification by research type of a study depends on a number of conditions.…”

Section: Conduction Phasementioning

confidence: 99%

Trends and Gaps in Ontology-Supported Environmental Health

Silva

Bulcão-Neto

2021

Anais Do XII Computer on the Beach - COTB '21

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Environmental Health (EH) refers to aspects of human health affectedby factors in the environment, e.g., biological factors, andit is an essential part of any comprehensive public health system.Similar to other health-related fields, one observes an increasingmovement in the adoption of IoT technologies into the EH domain.Regarding the data life cycle in IoT systems, data modeling andinterpretation are crucial tasks in which ontologies are a feasiblesolution because of their expressiveness and reasoning support.In this paper, we structure the ontology-supported EH researchtheme through a systematic literature mapping. The identificationand selection strategies of primary studies include the automaticsearch for studies published from 2010 to 2019 on five sourcesand the application of inclusion and exclusion criteria on an eighthundred-eleven-distinct-paper group. The results of this originalwork provide an overview of the research theme with multipleclassifications of thirty-four relevant studies remaining as well asthe finding of trends and gaps for future work.

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Section: Conduction Phasementioning

confidence: 99%

Trends and Gaps in Ontology-Supported Environmental Health

Silva

Bulcão-Neto

2021

Anais Do XII Computer on the Beach - COTB '21

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“…Online Environmental Report Cards Project provides GIS interfaces for online interactive access to integrated environmental monitoring data and environmental models, for both South East Queensland and the Great Barrier Reef, enabling decision support and adaptive resource management [19].…”

Section: E-researchmentioning

confidence: 99%

Data centric research at the University of Queensland

Zhou

Sadiq

2013

SIGMOD Rec.

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“…This additional layer of OGDL Framework can also be used to extract semantic cluster patterns of historical data and provide best-practice guidelines from evidence based knowledge repository as depicted in Figures 1 base layers. III. OGDL ADVANCEMENT TOWARDS FACETED SEARCH ENGINE AND DECISION SUPPORT DEVELOPMENT In light of approach used in [14], we extend our OGDL framework [11] in system architecture with QBE (Query-byExample) based querying, reporting and visualization interfaces that enable the identification of cluster quality and cluster mapping trends. We further extend our existing OGDL framework by proposing a Faceted Search Engine System that utilizes for the purpose of knowledge management.…”

mentioning

confidence: 99%

A framework of Ontology Guided Data Linkage for evidence based knowledge extraction and information sharing

Gollapalli

Xue

2013

2013 IEEE 29th International Conference on Data Engineering Workshops (ICDEW)

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There has been a surge of interests in developing probabilistic techniques for linking semantic equivalent datasets. The key objective is to transform the structure of the induced data into a concise synopsis. Current techniques primarily focus on performing pair-wise attribute matching and pay little attention in discovering direct and weighted correlations among ontological clusters through multi-faceted classification. In this research, we introduce a novel Ontology Guided Data Linkage (OGDL) framework for self-organising and discovering schema structures through constructing a hierarchical cluster mapping trees. Furthermore, we extend our OGDL framework by introducing a novel faceted search engine for semantic interoperability of data and subsequent decision support analysis, and use it to map fast cluster browsing, user friendly querying and semantic reasoning learning needs.

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

Abstract: The Health-e-Waterways Project is a multi-disciplinary collaboration between the University of Queensland

Cited by 11 publications

References 12 publications

Trends and Gaps in Ontology-Supported Environmental Health

Trends and Gaps in Ontology-Supported Environmental Health

Data centric research at the University of Queensland

A framework of Ontology Guided Data Linkage for evidence based knowledge extraction and information sharing

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