Digitalization of biological populations and ecosystems changes our relation towards them. In silico representations of natural systems make them available as resources that allow for novel ways of deriving economic value. These extracted data and models also open novel routes for responsible innovation based on biological systems and derived biological data. Responsible innovation based on natural resources is explored using the common pool resource framework and using the emerging field of biodiversity sequencing as an example. Natural systems that have a vast digital representation which is shared by a community have aspects from both a natural resource commons and from a knowledge commons, but differ in their structure and dynamics. We therefore propose the concept of 'Twin Commons': the institutional arrangement of natural resources that have a tightly linked digital component which is shared and governed by a community, and that have research and innovation as important outlets.

Synthetic biology, as an engineering approach to biological systems, has the potential to disruptively innovate the development of vaccines, therapeutics, and diagnostics. Data accessibility and differences in data-usage capabilities are important factors in shaping this innovation landscape. In this paper, the data that underpin synthetic biology responses to the COVID-19 pandemic are analyzed as positional information goods—goods whose value depends on exclusivity. The positionality of biological data impacts the ability to guide innovations toward societally preferred goals. From both an ethical and economic point of view, positionality can lead to suboptimal as well as beneficial situations. When aiming for responsible innovation (i.e. embedding societal deliberation in the innovation process), it is important to consider hurdles and facilitators in data access and use. Central governance and knowledge commons provide routes to mitigate the negative effects of data positionality.

No abstract