Data

To support construction managers in situational awareness and decision-making across different construction phases, it is essential to have formal, machine-readable, and interpretable knowledge models and tools. The objective is to develop a standardized and structured representation of project planning data, encompassing task, schedule, resource, and cost information, by creating three domain ontologies. These ontologies are critical as they provide vocabularies for translating data from proprietary formats to RDF triples. A prototype system was developed using Protégé, an open-source ontology editor, and Owlready2, a package for ontology-oriented programming in Python, to support data translation, querying, and information reasoning. A use case was applied and analyzed to demonstrate the effectiveness of the proposed exchange mechanism in facilitating machine-interpretable data.

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