This project is based on an opportunity to bridge an increased desire for architectural userevaluation in an industry context that currently does not allow it, and the somewhat precariousemployment situation a techno-anthropologist might find themselves in. Based on this, thisthesis is an attempt at experimenting with quali-quantitative analysis as a means to add a levelof scalability to qualitative architectural evaluation. As such, an experiment has beenconducted which seeks to fulfil said aim on the Lyngby campus of The Technical University ofDenmark with the employment of a mobile app directed at students. As a least-likely case, totest out the boundaries of delegating data collection to students and dedicated digitaltools—with the least in-situ involvement of a researcher. This way, the experiment contains thedouble aim of both producing insights about campus, but more importantly shedding light onthe challenges encountered along the way. The result of which has been many challenges, butlittle data. Despite this, doing quali-quantitative analysis in a ‘complementarity’-sense, hasproved to still be a viable option.As such, our project demonstrates a core challenge of data projects: aligning networkaffordances with the matters of concerns of all parties involved. Where our efforts oftranslation fell short, we encountered challenges with the following: our perceived legitimacy,owing to our role as students; the trade-off, of offering recruitment incentives external to thegoal of the evaluation itself; and by involuntarily relating ourselves to the existing datapractices of apps on smartphones. From this, we recommend a focus on achievingtransparency, when using dedicated digital tools for architectural evaluation—aiming atconcrete matters of concern of the participants you wish to engage with and putting specialeffort into communicating the outcomes of the evaluation. Based on this, as well as a widerdiscussion, we argue that the role of the researcher in data projects is much more than justattending to their own research interest: It is a matter of translating between tools, methods,participants and conflicting data conceptions—a marathon of interdisciplinarity.