Content
• Basic concepts: representation, format, model
• Levels of interoperability (technical, syntactic, semantic, pragrmatic)
• BIM and evolution of model data (stages/LODs)
• OpenBIM: IFC, BCF, bSDD, IDS
• Open tools: IfcOpenShell, That Open Engine
• City models: CityGML, CityJSON
• Linked data and granular representations (URI, RDF, SPARQL)
• Ontologies for built environment (OWL and established ontologies)
Learning objectives
The student
• can identify and explain the relevant machine understandable representations and formats used for entities of different scopes in built environments (building products, buildings, urban areas)
• understands how the models based on each representation are created
• can identity and explain the levels of interoperability within and between different representations
• understands the roles of application programming interfaces, data representations and formats, and query languages in accessing data
• understands how different representations can be interlinked
• can apply relevant programming tools to structure and utilise each of the representations
• can create software solutions utilising relevant representations.
Prerequisites
Programming skills in Python and Javascript sufficient to
• implement simple algorithms
• utilise libraries such as IfcOpenShell or That Open Engine
• access the APIs of systems providing data about built environment.
Teaching methods
Lectures, assignments, and the final exam.
A student needs to bring his or her own computer to the class.
Assignments will require Python programming skills.
Lectures will be available online in Teams and recorded to support independent study and review of learning content. The recordings will be available for the students of the course and/or the study programme through the Moodle platform until the additional exams have been completed. When a student does not want to be identified in the recordings, he or she can ask questions only through the chat.
Learning material and recommended literature
Provided during the course through the Moodle platform.
Study materials will consist of lecture slides, lecture recordings, and other supporting materials (for instance, specifications, standards, scientific or professional articles, links to tools or datasets, informative talks and other videos)
Evaluation criteria
Based on the exam (50%) and assignments (50%).
