What is a data model?

Abstract

Many decades ago Patrick Suppes argued rather convincingly that theoretical hypotheses are not confronted with the direct, raw results of an experiment, rather, they are typically compared with models of data. What exactly is a data model however? And how do the interactions of particles at the subatomic scale give rise to the huge volumes of data that are then moulded into a polished data model? The aim of this paper is to answer these questions by presenting a detailed case study of the construction of data models at the LHCb for testing Lepton Flavour Universality in rare decays of B-mesons. The close examination of the scientific practice at the LHCb leads to the following four main conclusions: (i) raw data in their pure form are practically useless for the comparison of experimental results with theory, and processed data are in some cases epistemically more reliable, (ii) real and simulated data are involved in the co-production of the final data model and cannot be easily distinguished, (iii) theory-ladenness emerges at three different levels depending on the scope and the purpose for which background theory guides the overall experimental process and (iv) the overall process of acquiring and analysing data in high energy physics is too complicated to be fully captured by a generic methodological description of the experimental practice.

Simulated Data in Empirical Science

“…As Parker (2016) notes, reanalysis data is not self-evidently less reliable than empirical data. This is a general feature of simulated data that holds in a variety of cases: Several recent contributions have argued against the idea that the epistemic reliability of data is highest when they are unprocessed ("pure" or "raw") (Antoniou, 2021;Bokulich, 2021;Bokulich & Parker, 2021;Humphreys, 2014). Simulation is often used to generate better data models.…”

“…We aim to show the conditions under which simulated data can be used to provide better data-to-phenomena inferences. Antoniou (2021) posits that a dataset is epistemically reliable if it provides correct information for the physical phenomenon it represents. Similarly, one can ask: When is a simulated dataset epistemically reliable?…”

Robustness and Dark-Matter Observation

“…These three categories of factors are not always entirely independent of each other; however, this categorization is helpful to illustrate how the extraction of information from an observational method is conditional on a number of assumptions of different origin.13 SeeGueguen (2020) andSmeenk and Gallagher (2020) for some nice discussions on the use of simulation in cosmology.14 For more detailed discussions on the impact of experimental models on the final results of an experiment, seeAntoniou (2021) andStaley (2020).…”

“… 14 For more detailed discussions on the impact of experimental models on the final results of an experiment, see Antoniou (2021) and Staley (2020). …”