Benefit sharing: Why inclusive provenance metadata matter

Abstract

Fair and equitable benefit sharing of genetic resources is an expectation of the Nagoya Protocol. Although the Nagoya Protocol does not yet formally apply to Digital Sequence Information ("DSI"), discussions are currently underway regarding to include such data through ongoing Convention on Biological Diversity ("CBD") negotiations. While Indigenous Peoples and Local Communities ("IPLC") expect the value generated from genomic data to be subject to benefit sharing arrangements, a range of views are currently being expressed by Nation States, IPLC and other stakeholders. The use of DSI gives rise to unique considerations, creating a gray area as to how it should be considered under the Nagoya Protocol's Access and Benefit Sharing ("ABS") principles. One way for benefit sharing to be enhanced is through the connection of data to proper provenance information. A significant development is the use of digital labeling systems to ensure that the origin of samples is appropriately disclosed. The Traditional Knowledge and Biocultural Labels initiative offers a practical option for data provided to genomic databases. In particular, the BioCultural Labels ("BC Labels") are a mechanism for Indigenous communities to identify and maintain provenance, origin and authority over biocultural material and data generated from Indigenous land and waters held in research, cultural institutions and data repositories. This form of cultural metadata adds value to the research endeavor and the creation of Indigenous fields within databases adds transparency and accountability to the research environment.

Keywords: BC labels; DSI; Indigenous; TK labels; benefit sharing; metadata; provenance; traditional knowledge.

FIGURE 1

DSI policy options (United Nations Convention on Biological Diversity Open Ended Working Group, 2021).

FIGURE 2

Example FASTA sequence with BC Multiple Communities Label as provenance information included in the header. Provenance information can be appended using the R package enRich (https://github.com/jacobgolan/enRich).