starting point: 

How is design data stored, made accessible, or secure, and what are the practical, legal, ethical, and commercial frameworks that allow or prevent the use of architectural data?  

This topic may include consideration of: the potential benefits and limits of current practice, the relevant timescales (years / decades) for different data uses (circular economy) and types of users (individual/society). 

project summary: 

The rapid digitalisation of the architectural, engineering, and construction (AEC) industries has significantly increased the value of data in the sector (Ahmed et al., 2018). However, managing this data remains a complex challenge due to its heterogeneous nature. Digital data has been integral to projects since the introduction of Building Information Models (BIM), which serve as a data management strategy in the sector (Hu et al., 2022). This embedded data from the design phase is stored in companies’ archives as knowledge that has the potential to inform and improve design decisions (Howard, 1991).  

AEC professionals face challenges not only in how to manage, extract, and utilise digital data (Bilal et al., 2016) but also in how to leverage it to minimise the environmental impact caused by AEC practices (Ghafoor et al., 2023). To address this, data circularity (Sen, 2023) emerges as a novel approach to data management and use within the circular economy framework (Ellen MacArthur Foundation, 2025). This approach contemplates data as an independent asset with intrinsic value, allowing for its enhancement through various strategies such as reuse, relearning, repurposing, reduction, and disposal [Figure 1].  

Figure 1 Circular Economy, Desirable Circular Cycle. Compilation of technical and biological cycle and the inclusion of the Digital Cycle with its strategies (Personal interpretation). 

This research aims to improve the effectiveness of early design decisions by providing meaningful insights using data extracted from existing projects. Emphasises on the early stages of a project (from both structural and design aspect), where key decisions can be made with minimal impact on the overall budget and timeline and maximum influence on the outcome (Mc Leame Curve, 2004).  

To achieve this goal, the research methodology combines two approaches: action design research, which involves collaboration with industry partners from the early stages (Arch_Manu), and speculative design (Dunne & Raby, 2014) [Figure 2], which offers a critical perspective on how data can influence future design decisions in the AEC industry. This methodology will be applied using a ‘petri dish’ scheme, where small projects will be developed and tested to verify the research hypothesis. The outcomes of this scheme will be validated in collaboration with industry partners on a real project.  

Figure 2  Research Strategy. Past – Present – Future Strategy. Illustrate the flow of knowledge, the methods used and the stages of the research methodology., it will be explain in detail in the section 3.1 The Methodology + Overview of the Iterative cycle 

Ultimately, the study emphasises that integrating data circularity into AEC design processes can lead to more accurate and efficiency early design decisions by improving data communication, thus promoting sustainable design practices within the AEC sector. 

References

• Ahmed, V., Aziz, Z., Tezel, A., & Riaz, Z. (2018). Challenges and drivers for data mining in the AEC sector. Engineering, Construction and Architectural Management, 25(11), 1436–1453. https://doi.org/10.1108/ECAM-01-2018-0035 

• Bilal, M., Oyedele, L. O., Qadir, J., Munir, K., Ajayi, S. O., Akinade, O. O., Owolabi, H. A., Alaka, H. A., & Pasha, M. (2016). Big Data in the construction industry: A review of present status, opportunities, and future trends. Advanced Engineering Informatics, 30(3), 500–521. https://doi.org/10.1016/j.aei.2016.07.001 

• Dunne, A., & Raby, F. (2014). Speculative everything, design, fiction and social dreaming. 

• Ellen MacArthur Foundation. (2025). Circular Economy. https://www.ellenmacarthurfoundation.org/ 

• Ghafoor, S., Hosseini, M. R., Kocaturk, T., Shooshtarian, S., Arnel, T., King, D., Bonsey, J., & Garofano, N. (2023). Unlocking the Power of the Circular Economy in the Australian AEC Industry: A Journey through Attitudes, Barriers and Enablers. 

• Howard, H. C. (1991). Project‐Specific Knowledge Bases in AEC Industry. Journal of Computing in Civil Engineering, 5(1), 25–41. https://doi.org/10.1061/(ASCE)0887-3801(1991)5:1(25) 

• Hu, Z.-Z., Leng, S., Lin, J.-R., Li, S.-W., & Xiao, Y.-Q. (2022). Knowledge Extraction and Discovery Based on BIM: A Critical Review and Future Directions. Archives of Computational Methods in Engineering, 29(1), 335–356. https://doi.org/10.1007/s11831-021-09576-9 

• Sein, M., Henfridsson, O., Purao, S., Rossi, M., & Lindgren, R. (2011). Action Design Research. MIS Quarterly, 35, 37–56. https://doi.org/10.2307/23043488 

• Sen, D. (2023). What is data circularity, and why should you care? https://dataroots.io/blog/what-is-data-circularity-and-why-should-you-care