Abstract
The creation and use of ontologies has become increasingly relevant for complex systems in recent years. This is because of the growing number of use of cases that rely on real-world integration of disparate systems, the need for semantic congruence across boundaries and the expectations of users for conceptual clarity within evolving domains or systems of interest. These needs are evident in most spheres of research involving complex systems, but they are particularly apparent in infrastructure and cities where traditionally siloed and sectoral approaches have dominated, undermining the potential for integration to solve societal challenges such as net zero, resilience to climate change, equity and affordability. This paper reports on findings of a literature review on infrastructure and city ontologies and puts forward some hypotheses inferred from the literature findings. The hypotheses are discussed with reference to the literature and provide avenues for further research on (a) belief systems that underpin non-top-level ontologies and the potential for interference from them, (b) the need for a small number of top-level ontologies and translation mechanisms between them and (c) clarity on the role of standards and information systems in the adaptability and quality of data sets using ontologies. A gap is also identified in the extent that ontologies can support more complex automated coupling and data transformation when dealing with different scales.
Original language | English |
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Pages (from-to) | 43-52 |
Number of pages | 10 |
Journal | Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction |
Volume | 176 |
Issue number | 2 |
Early online date | 26 Jul 2022 |
DOIs | |
Publication status | Published - 1 Jun 2023 |
Externally published | Yes |
Keywords
- artificial intelligence
- city-scale infrastructure operations
- city-scale simulations & data analytics
- critical infrastructure
- data
- data analytics for infrastructure
- digital twin
- information technology
- infrastructure planning
- modelling
- UN SDG 9: Industry, innovation and infrastructure
- urban infrastructure development