We report the experience of the FucoSan InterReg project that had the ambition to generate commercialization opportunities for biotechnology research in a marine environment. Fucoidan, a promising biomarine polysaccharide extracted from seaweed, offers a broad array of potential applications; however, the supporting innovation value chain is still under development. We explore how the use of business modelling tools can contribute to building a shared understanding of commercialization opportunities across a diverse range of research and development actors. We analyze data (interviews, workshops, and surveys) from a German-Danish network of actors involved in the FucoSan InterReg project to identify how the tools contribute to setting up a base to support future activities across a potential innovation value chain. The results point towards the direct and indirect positive effects of engaging in the co-creation of a shared understanding of the functionality and possibilities of promising biomarine products. The findings support the idea that interdisciplinary and multilateral interactions help actors to identify the necessary connections and interdependencies to build a sustainability-driven innovation value chain.

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Open data platforms are interfaces between data demand of and supply from their users. Yet, data platform providers frequently struggle to aggregate data to suit their users’ needs and to establish a high intensity of data exchange in a collaborative environment. Here, using open life science data platforms as an example for a diverse data structure, we systematically categorize these platforms based on their technology intermediation and the range of domains they cover to derive general and specific success factors for their management instruments. Our qualitative content analysis is based on 39 in-depth interviews with experts employed by data platforms and external stakeholders. We thus complement peer initiatives which focus solely on data quality, by additionally highlighting the data platforms’ role to enable data utilization for innovative output. Based on our analysis, we propose a clearly structured and detailed guideline for seven management instruments. This guideline helps to establish and operationalize data platforms and to best exploit the data provided. Our findings support further exploitation of the open innovation potential in the life sciences and beyond.