Author(s): Lijun Wei, Heshan Du, Quratul-Ain Mahesar, Barry Clarke, Derek R. Magee, Vania Dimitrov, David Gunn, David Enwisle, Helen Reeves, Anthony G. Cohn
Abstract: Sustainable subsurface infrastructure management requires an integrated approach that considers the various city infrastructure assets (e.g. roads, ground, buried utilities), human activities and the environment as a holistic system. To this end, an integrated knowledge-driven decision support system is presented in this paper based on a suite of knowledge models, which describe the main properties/processes of different city infrastructure assets (City Infrastructure Asset Ontologies), the categories/ properties of events that need some decisions to be made in assets management (Trigger Ontology), and the geophysical techniques suitable for measuring different asset properties (Investigation Ontology). Various datasets are sourced, preprocessed, integrated in a spatial database and mapped to these ontologies; and an inference engine is employed to exploit the knowledge and data for automated inference of potential consequences. A prototype of this system has been developed and users’
feedback collected from two workshops showed that the system is widely considered as a potentially useful tool for practitioners.
Keywords: knowledge-driven; data integration; reasoning; decision support system; subsurface infrastructure management; inter-asset management