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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. [ABSTRACT FROM AUTHOR]

This is a state-of-the-art assessment for a small but burgeoning research approach, use of curricula vitae in research evaluation. The accumulated research remains sufficiently modest for us to consider nearly all published studies and the full range of research purposes to which CV analysis has been applied. CV analysis has been theory-driven, and theory and tools have increasingly converged. Advances in method and technique have been abetted especially by the push for a scientific and technical human capital theory to explain the role of capacity in research evaluation. We summarize the theoretical rationale for CV analysis, and present three major foci: career trajectories, mobility, and the mapping of collective capacity. We assess progress in solving methodological and practical problems and the future research possibilities and remaining needs in developing methods. We reflect on some new research topics that could benefit from CV analysis. We draw on the papers in this special issue of Research Evaluation to illustrate research developments and to show the place of specific contributions in the developing CV literature. [ABSTRACT FROM AUTHOR]

This paper stems from an interest in assessing and encouraging the efficiency of the grant peer-review system in Spain. We use the curricula vitae submitted to the Ministry of Education and Science by a sample of applicants to the Ramón y Cajal Programme to build statistical discriminatory models that successfully replicate the outcomes and rankings produced by the peer-review process. The results of this exercise seem to show that the selection process mainly relies on the research productivity of applicants and not on other variables not directly related with scientific excellence such as gender, age or residence. Furthermore it suggests that electronic discriminatory tools could be further developed and used in the future to support and speed up the process of evaluation and selection of applicants. [ABSTRACT FROM AUTHOR]

Relying on the international literature on CV-based indicators, we select a sample of CVs from researchers applying to the Spanish Ramón y Cajal programme to assess mobility patterns and look for evidence of links between mobility and research performance. Evidence is found that mobility patterns vary across disciplines and that most internationally mobile researchers seem to have better access to international funding sources and networks, which does not, however, imply that they are the most quantitatively productive as far as publications and patents are concerned. The results thus support the idea that the qualitative dimension of mobility impact is an important one to consider. [ABSTRACT FROM AUTHOR]