This paper focuses on inter-organizational R&D collaborations as captured by joint research projects funded within the European Framework Programmes for Research and Technological Development (EU-FPs). We identify determinants of collaboration, including actor characteristics, relational and network effects as well as geographical effects by means of a discrete choice model. Using data on EU-FP projects from the EUPRO database and from a representative survey of participants, we produce statistically significant evidence that collaboration choices in EU-FPs are primarily facilitated by prior acquaintance, thematic proximity and geographical proximity. Also, network effects are significantly related to collaboration choice. Moreover, the study shows that the impact of geographical effects increases for more intensive collaboration. The results are promising since a deeper understanding of these collaboration processes is needed for future governance of research policies in the EU.

The principles of Findability, Accessibility, Interoperability, and Reusability (FAIR) have been put forward to guide optimal sharing of data. The potential for industrial and social innovation is vast. Domain-specific metadata standards are crucial in this context, but are widely missing in the energy sector. This report provides a collaborative response from the low carbon energy research community for addressing the necessity of advancing FAIR metadata standards. We review and test existing metadata practices in the domain based on a series of community workshops. We reflect the perspectives of energy data stakeholders. The outcome is reported in terms of challenges and elicits recommendations for advancing FAIR metadata standards in the energy domain across a broad spectrum of stakeholders.

R&D collaboration networks stimulated by the European Union in its Framework Programs (FP) on Research and Technological Development exhibit - like many other large social networks - characteristic features of complex networks. Existing analyzes of these networks, however, are mostly built on strongly simplifying assumptions for network construction, like fully connected project graphs or star-graphs. Still, apart from qualitative evidence, little is known about the determinants that affect partner choice and network dynamics. It is the aim of this paper to provide empirical evidence for a more differentiated picture of partner selection - and thus network formation - in the European FPs. We adopt an econometric perspective to identify determinants of link formation, including various actor characteristics, relational and network effects as well as geographical effects. We employ a binary choice model estimated by means of logistic regressions, with a dependent variable that represents the establishment of a formal cooperation between two organizations in FP5. We use data on EU FP projects from the sysres EUPRO database and from a representative survey of FP 5 participants. The study produces statistically significant evidence that R&D collaboration choices of organizations participating in European FPs are affected by geography, FP experience and relational factors including network characteristics. Thematic proximity matters more than geographic proximity, while most influential for collaboration appears to be prior acquaintance of the actors. Also, network effects significantly determine the collaboration choice, but to a slightly smaller extent than geographical effects.