Knowledge scales through translation. Sabina Leonelli's epistemology of data treats data as objects whose evidential capacities are produced through movement, processing and reuse. A datum collected in one setting changes epistemic identity when it enters another dataset, discipline, model or institutional problem. Data Journeys traces these transformations from material encounters through classification, cleaning, aggregation, visualisation, databases and archives. Mobility depends on infrastructures and on decisions about which attributes must remain attached to an object for it to continue functioning as evidence. "What Distinguishes Data from Models?" locates the distinction between data and models in epistemic role. Data are organised to support claims. Models are constructed to represent phenomena. The boundary is functional and situated, fixed by use rather than by intrinsic form. "Where Health and Environment Meet" converts spatiality into an epistemological problem. Geolocation operates as an invariant that links heterogeneous datasets, and its stability depends on attention to resolution, time, provenance and purpose. Scale functions as one of the operations that modifies evidential scope. The concept of research environments extends this logic to science itself: instruments, institutions, skills, administrative structures, disciplinary arrangements and social norms condition which evidential journeys are possible and which forms of knowledge can emerge. A spatial field built from neighbourhoods, metropolitan comparisons and open repositories uses this epistemology as a discipline of translation. Socioplastics specifies the conditions under which evidence moves between scales: what remains invariant, what must be recalibrated, what metadata travel with an object, and where comparison becomes illegitimate. The transition from individual experience to neighbourhood condition, metropolitan comparison and territorial synthesis carries hidden epistemic operations at every step. Perceived restoration requires disaggregation before it enters an urban-quality index. Heat measurements acquired under different temporal regimes require recalibration before they support comparable exposure claims. A walking observation carries embodied and spatial relations that a point coordinate cannot register. A method developed in Madrid requires translation before it supports a claim in Dakar, Rotterdam or Oulu. Open science intensifies these problems. Making objects publicly accessible increases the probability of reuse outside their original research environments. The corpus therefore requires a visible architecture of provenance, transformation, validity and versioning. This architecture allows evidence to travel while registering that mobility transforms it. The result is a theory of scale as epistemic transformation: knowledge expands only when the conditions of translation remain legible. Within Socioplastics, this disciplined mobility condenses as UncertaintyPassage.
Anto Lloveras is an architect and urban researcher whose work connects spatial evidence, comparative urbanism, epistemology, archives and public research infrastructures through LAPIEZA LAB and Socioplastics.
Leonelli, S. (2016) Data-Centric Biology: A Philosophical Study. Chicago: University of Chicago Press.
Leonelli, S. (2019) 'What Distinguishes Data from Models?', European Journal for Philosophy of Science, 9, article 22.
Leonelli, S. and Tempini, N. (eds.) (2020) Data Journeys in the Sciences. Cham: Springer.
Leonelli, S. and Tempini, N. (2021) 'Where Health and Environment Meet: The Use of Invariant Parameters in Big Data Analysis', Synthese, 198(Suppl 10), pp. S2485–S2504.
Leonelli, S. and Trappes, R. (2026) 'The Nature of Research Environments: Editorial Introduction', European Journal for Philosophy of Science, 16, article 45.
