On the need for caution in using ‘big data’ for built environment research: A response to Chng et al. (2024)

The study of the built environment is evolving with digital advancements and the emergence of a big data era, opening up new possibilities for planning practice and research. However, the integration of digital tools in research and practice calls for consideration of methodological questions. In this article, we compare two studies. One is our own ‘small data’ case study research and the other is a ‘big data’ approach recently published in this journal. Both studies discuss housing space standards – internal floorspace – in the context of a deregulated planning policy known in England as ‘permitted development’ (PD) relating to office-to-residential conversion schemes. Not only do these studies differ methodologically but also in results: our own case studies found that the majority of PD housing units do not meet recommended space standards. This finding is consistent with other in-depth studies on the same issue but is contradicted by the big data study that yielded different results. By reference to example conversion schemes, we argue that to understand the space standards issue, a more in-depth small data approach is more reliable than relying solely on secondary data sets and a big data approach. This illustrates a need for wider debate as to when big data is beneficial and when it can be misleading, particularly if being utilised to criticise evidence from alternate, more detailed data approaches. We conclude that it is crucial that academic discussions on different methodological approaches are conducted with respect, openness and transparency regarding the suitability of different approaches.