Resource bias: a study of choice in the data collection for Digital Twins

It is often suggested that data collection is the mining of a natural resource. But data are not lying around, waiting to be collected. Collecting them demands choices about the software to use, hardware, the measuring system, the form that information gets (numbers, text) etc. How are these choices made?

The goal of the project is to identify the different choice-makers and the choices that they make in order to shape the databases on which the Digital Twin is based, and distinguish possible bias in these choices.

The project will consist of desk-research and interviews, and will adopt a social-empirical perspective. The desk-research shall mainly focus on literature from Science and Technology Studies, sociology, and media theory scholars and functions as the theoretical background for the interviews and critical analysis. This literature study is supposed to provide insight into how the selection of data-inputs on which digital technology is based can produce bias. For the interviews we are looking to interview the project leaders as well as those working on the data collection and databases of all three flagship projects. The main purpose is to get a view on who the choice-makers are and how they make the choices regarding the data collecting and structuring of the digital twins. We will give special attention to the societal aspects that the choice-makers take into account when they select the data.

The conclusions of this study will offer a foundation for the further development of guidelines for Responsible Research and Innovation in Digital Twin design for the agrifood sector and life sciences, and material for a possible subsequent academic article.