Knowledge management for more sustainable water systems


The management and sharing of complex data, information and knowledge is a fundamental and growing concern in the Water and other Industries for a variety of reasons. For example, risks and uncertainties associated with climate, and other changes require knowledge to prepare for a range of future scenarios and potential extreme events. Formal ways in which knowledge can be established and managed can help deliver efficiencies on acquisition, structuring and filtering to provide only the essential aspects of the knowledge really needed. Ontologies are a key technology for this knowledge management. The construction of ontologies is a considerable overhead on any knowledge management programme. Hence current computer science research is investigating generating ontologies automatically from documents using text mining and natural language techniques. As an example of this, results from application of the Text2Onto tool to stakeholder documents for a project on sustainable water cycle management in new developments are presented. It is concluded that by adopting ontological representations sooner, rather than later in an analytical process, decision makers will be able to make better use of highly knowledgeable systems containing automated services to ensure that sustainability considerations are included.

Divisions: College of Business and Social Sciences > Aston Business School
College of Business and Social Sciences > Aston Business School > Operations & Information Management
College of Business and Social Sciences > Aston Business School > Advanced Services Group
Additional Information: © 2010 The authors. This is an open access article distributed under the terms of the Creative Commons Attribution 3.0 unported (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Uncontrolled Keywords: ontologies,text mining,water cycle management,Civil and Structural Engineering,Building and Construction,Computer Science Applications
Publication ISSN: 1403-6835
Last Modified: 06 May 2024 07:10
Date Deposited: 04 Feb 2015 16:30
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Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Special issue
Published Date: 2010-02-17
Authors: Mounce, S.R.
Brewster, C. (ORCID Profile 0000-0001-6594-9178)
Ashley, R.M.
Hurley, L.



Version: Published Version

License: Creative Commons Attribution

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