Opening the black box: an explanatory model of data reuse in health research and beyond

Previous studies on the use of secondary data – or data reuse – found that researchers confront considerable (un)foreseen challenges related to finding, accessing, decoding, and recontextualizing secondary data. However, why some researchers persist in this endeavor while others do not is unclear. We develop a plausible theoretical explanatory model – the data-reuse mechanism of this phenomenon. This model captures the relational aspects of the different elements involved in the process, i.e. scientific horizon and reward system, researcher’s cognitive frameworks and relational structures, the properties and relational structure of data, specific conditions, and time. We argue that it is the interaction among these elements that ultimately allows the researcher to decide about data reuse. Guided by this model, we analyze the data reuse process in ten molecular/computational biology and epidemiology case studies. The results of our analysis show how the intertwined synchronic and diachronic relations among these elements add considerable uncertainty to the reuse process. It is precisely this uncertainty combined with researchers’ tenacity, scientific horizon, and flexibility in changing this horizon that enable data reuse. Our findings demonstrate also that while some data properties such as open access may facilitate data reuse, they do not fully determine whether data are reused.