The emergence of open science and new data practices is changing the way research is done. Opportunities to access data through purpose built platforms and repositories, combined with emerging data and meta-data curation practices are expanding data availability in many fields. This paper presents a conceptual framework for studying scientific research careers, motivated by opportunities to link empirical datasets to construct new analyses that address remaining and emerging knowledge gaps. The research career conceptual framework (RCCF) emerges from a review of relevant theories and empirical findings regarding research careers. The paper reviews existing models and develops a typology of research careers. It also compiles a list of variables drawn from the literature on research careers. Two preliminary demonstrations of linking datasets to address empirical questions are outlined. The final discussion advocates an approach to emerging data opportunities that combines theories and models with empirical research questions as being superior to an approach that produces ad hoc explanations on the basis of ‘data fishing’ exercises.
A conceptual framework for studying science research careers
Carolina Cañibano, Richard Woolley, Eric J. Iversen, Sybille Hinze, Stefan Hornbostel, Jakob Tesch
The Journal of Technology Transfer