To improve the quality of life of communities, local government provides municipal services, including the sewer collection, effectively and efficiently employing asset management best practices. The condition assessment of assets (including the sewer collection system) is one of the core elements of implementing effective asset management across the utility organizations. Availability of sophisticated and complex condition assessment technologies, lack of common understanding about them and related high cost associated with sewer condition assessment requires the technologies and related knowledge to be explicitly defined in a neutral format-the ontology, to support the development of applications for technology selection. An ontology of condition assessment technologies for sewer network, CATS_Onto was developed following a seven-step approach at two levels of abstraction: meta-model and detailed ontology. This paper presents the development and verification of the meta-model. The proposed ontology will be used to develop a tool for the selection of the most appropriate technology for sewer condition assessment. The knowledge representation was verified while validation is underway.
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