Résumé

Urbanization and condensation of habitants per m2 have led to an intense use of subsurface volumes as construction space. Planning and constructing in such spaces is a very challenging task, since knowledge of existing objects is fragmentary and imprecise. An intelligent identification of present objects and thereby detecting available volumes would increase the design quality of projects, since incidents reported during field excavations (Tanoli et al., 2019) are numerous and costly. Combining existing official territorial data with intelligent methods for information completion, compliance checking and data management, is a promising approach as it has been partially demonstrated by the use of ontologies (Caselli et al., 2020; Métral et al., 2020). The minimum level of necessary information for a model-checking framework is identified and formalized by an ontology. The ontology then serves as a basis schema for a triple store database, storing data, completion and compliance rules. The process of data completion allows to qualify the confidence in spatial information delivered.

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