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he topic of biobanking has been anchoring in the world and Europe as well. The biobanking field today is characterised by heterogeneous entities that could be classified according to many different categories. This article aims to outline the process of the gradual embedding of the field of biobanking in the European Union (EU) from the point of view of the number of high-quality international research projects related to biobanking or biobanks as such. To identify these research projects, data from the European Commission's (EC's) database on research and innovation projects financed from Framework Programmes (FPs) of the European Union and the Horizon programme were used. It was found that the number of research and innovation projects in which biobanks played an important role more than doubled between 1994 and 2021. The highest increase in the number of biobank-related research and innovation projects occurred between 2002 – 2006 and 2007 – 2013. Several leading countries, in terms of the number of biobank related research projects, emerged during the whole period. The main actors were all countries of western Europe, characterised mostly by above-average performance in indicators such as GDP per capita, Human Development Index (HDI) or Euro Health Consumer Index (EHCI).

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INTRODUCTION: Industry 4.0 is a concept covering various research areas. Their development depends on the cooperation among several stakeholders, particularly public R&D (Research and Development) organisations.OBJECTIVES: This article aims to provide a mapping of informal strategic R&D partnerships of public R&D organisations in an ambiguously defined area of Industry 4.0.METHODS: Scientific collaboration mapping method based on self-identification is used. Moreover, social network analysis is used to discuss patterns and specific characteristics of this network. Empirical data are gathered through a questionnaire survey focused on managers of RD teams in the Slovak Republic.RESULTS: The resulting network of public R&D organisations operating in the field of Industry 4.0 in the Slovak Republic is connected, though characterised by low density. Intra-regional cooperation prevailed only in the region of the capital city. In other regions, cross-regional cooperation was dominant. Most cooperations occur between universities; cooperation between faculties and within one faculty is less frequent. Key teams of the network were identified based on their performance in three selected indicators of centrality. Three of them represented the first layer or core of the network.CONCLUSION: Within the network, active actors with a high number of cooperation and those located in its network centre who can support knowledge transfer across the identified R&D network are crucial. Our results confirmed that several variables are important to creating new collaborations and thus not limited to geographical proximity, institutional affinity and size of the workplace.