Smart cities utilize Big Data and IoT to provide a better life for citizens. Since they are the most complicated human artefact, the adoption of such technologies become a complex task, requiring continuous data collection, aggregation and analysis. In order to transform city problems into concrete actions, a systematic approach aimed at digital transition needs to be followed. There are huge efforts to build city information models for encoding city objects, their relations and supporting the decision-making. This requires a common knowledge base, supported by rich vocabularies and ontologies that are capable to handle information diversity and overload.

In this paper, a methodological framework and an upper-level ontology for building digital city models are presented. The process of digital city modelling follows the concept of digital twin by providing data-driven decision making. The proposed upper-level ontology aims to overcome city modelling problems due to data silos and lack of semantic interoperability.

Ahram T., Taiar R., Langlois K., Choplin A. (eds) Human Interaction, Emerging Technologies and Future Applications III. IHIET 2020. Advances in Intelligent Systems and Computing, vol 1253. Springer, Cham, pp. 384-390.