A Material-Relational Ontology of Data: Addressing Ethical Challenges in Psychological Research in a Data-Driven Era

Abstract

The shift to a society organized around digital data has come with significant-although sometimes still underappreciated-implications for psychological research. In part, this is owed to the narrowness of discussions about data ethics in the discipline, although also to the ontological assumptions about data that implicitly shape researchers' discussions and practices. The prevailing representationalist ontology of data-understanding data to be a passive abstraction that represents some preexisting phenomenon-draws researchers' attention to methodological issues, such as data quality, while simultaneously turning attention away from different kinds of issues. Informed by feminist technoscience and feminist-new-materialist thinkers, we argue for an alternative ontology of data that helps understand it as being material-relational-as something that is active and entangles researchers in (often invisible) relations that have real, material consequences. These ontological commitments can draw attention to those relations and their implications and help researchers consider what ethical issues are at stake, thus creating the conditions to advocate for new kinds of responsible research practices. We put this ontology to work by looking at two issues: the labor problems from data collection on MTurk and the environmental impacts of data storage. We conclude by offering practical recommendations for more responsible data practices in psychology.

The authors' abstract, as published at the source. Perspectives on Psychological Science, 2026 · DOI ↗