Digital twins and artificial intelligence depend on a less visible yet decisive factor: data quality. DTERBIM’s experience highlights why this challenge is essential to the digitalisation of the sector.
In an interview published by the European DTERBIM project, Dimitrios Rovas, Professor of Building Simulation and Optimisation at University College London (UCL), draws attention to an aspect that is often overlooked in discussions on digitalisation: the quality of the data underpinning BIM models. While technologies such as artificial intelligence and digital twins attract considerable interest, their effectiveness largely depends on the underlying information being consistent, complete and verifiable.
UCL’s contribution to the project focuses on defining processes, information requirements and quality assurance mechanisms that enable the development of more reliable and reusable digital models. The aim is to reduce errors, improve interoperability between tools and ensure that data can be used consistently throughout the entire lifecycle of buildings.
Rovas’ reflections point to a shift in the way the digital transformation of the built environment is approached. Beyond the development of new technologies, the real challenge lies in ensuring that the information on which decisions are based is robust and traceable.
