Seeing oneself as a data reuser: How subjectification activates the drivers of data reuse in science

Considerable resources are being invested in strategies to facilitate the sharing of data across domains, with the aim of addressing inefficiencies and biases in scientific research and unlocking potential for science-based innovation. Still, we know too little about what determines whether scientific researchers actually make use of the unprecedented volume of data being shared. This study characterizes the factors influencing researcher data reuse in terms of their relationship to a specific research project, and introduces subjectification as the mechanism by which these influencing factors are activated. Based on our analysis of semi-structured interviews with a purposive sample of 24 data reusers and intermediaries, we find that while both project-independent and project-dependent factors may have a direct effect on a single instance of data reuse, they have an indirect effect on recurring data reuse as mediated by subjectification. We integrate our findings into a model of recurring data reuse behavior that presents subjectification as the mechanism by which influencing factors are activated in a propensity to engage in data reuse. Our findings hold scientific implications for the theorization of researcher data reuse, as well as practical implications around the role of settings for subjectification in bringing about and sustaining changes in researcher behavior.

Automated summary

Considerable resources are being invested in strategies to facilitate data sharing in scientific research, but the factors influencing researcher data reuse are not well understood. This study highlights the role of subjectification in activating the influencing factors and characterizes the relationship between these factors and research projects. The findings suggest that project-independent and project-dependent factors have an indirect effect on recurring data reuse through subjectification. These findings have scientific and practical implications for understanding and promoting researcher data reuse.