DataMines combines approaches from STS, critical data studies, and political ecology, and develops “track and tracing” ethnographic methods to follow the flow of genetic resources across land, oceans, jurisdictions, and global databases. It builds on a collaboration between the University of Oslo, Fridtjof Nansens Institute, and the University College London, and it brings together an interdisciplinary team of international scholars in Europe and Brazil. The project is led by Associate Professor Ana Delgado.
Biodiversity loss is a main global challenge. DataMines addresses it by studying how genetic resources are digitalized and increasingly stored in and retrieved from databases, often as open data. The project analyses the challenges that turning biodiversity into data poses for biodiversity governance. It focuses on bioprospecting, i.e. the search for commercially interesting forms of biochemistry nature. Using an ethnographic approach it follows specific forms of biodiversity (plants and microbes) in Brazil and Norway.
The digital shift in bioprospecting poses several challenges to existing regulatory mechanisms for the fair access and use of genetic resources. Genetic data on critical biodiversity resources accumulate in databases in the Global North, even when that data has been collected from organisms and microorganisms in megadiverse countries in the Global South.
The digitalization of bioprospecting, including the use of AI and datamining software to search for interesting sequences in databases, has opened up a new round of global controversies on genetic-resource extraction and exploitation, including what indigenous and activist groups see as a new form of digital biopiracy. A key problem is that regulatory and legal mechanisms are missing to regulate the flow of data, and to govern databases.
How does the governance of resource extractions change when the site of extraction is not only physical sites existing within national jurisdictions, but when resources also exist as data in databases and clouds? The project DataMines addresses this question, to produce theoretical and empirical knowledge that can be used to inform better policies, towards contributing to data sovereignty and environmental justice.
Tagged as: Life Sciences
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