24/09/2026
We are happy to share a new publication from the QuiVal consortium!
The paper, “The interoperability of digital technologies for the reuse of the building stock: A systematic literature review”, is authored by bayo windapo (DC13) and published in the Developments in the Built Environment (Journal of Elsevier).
This paper is the first journal publication of Bayo’s PhD thesis, written as a first-author collaboration with Oceane Durand-maniclas and our co-authors Ioanna Mitropoulou, Deepika Raghu, Claudio Martani, Carl Haas, and Catherine De Wolf.
📍What is the paper about?
Data scarcity currently hinders decision-making about the value and reusability of existing buildings and their components.
The paper reviews synthesises how digital technologies are used to gather, process, and store and share data for the reuse of existing building stock. The paper identifies 9 workflow clusters that summarise the various ways digital technologies have been used to manage existing building data and highlights key knowledge gaps for future technical research:
🔸First, current digital workflows reveal a data-processing bottleneck, particularly in scan-to-BIM workflows, where laser scan data are commonly processed manually to generate BIM models without any scalable methods to extract geometric data from point clouds.
🔸Second, 65% of the data outputs produced by the observed digital workflows focus primarily on physical data, particularly geometry, with limited research into extracting mechanical, economic, environmental, chemical, and temporal data, which are also important for reusing existing buildings.
🔸Third, workflow interoperability is limited by fragmented data formats that do not sufficiently support data exchange between systems.
The work is a collaboration between the Chair of Circular Engineering for Architecture at ETH Zürich and Department of Civil and Environmental Engineering - University of Waterloo. The research has received funding from the European Union’s Horizon Europe research and innovation programme under the Marie Skłodowska-Curie grant agreement No 101169048 (QuiVal ).
📄 Read the full open-access paper here:
