ABSTRACT
Given the new opportunities for data-driven research afforded by genomics in conjunction with bioinformatics, biologists and their sponsors have been struggling for agreement on data dissemination strategies. The factors involved in regulating the disclosure and circulation of genomic data range from the conflicting interests and ethos of the researchers involved to the clash in goals and procedures characterising biotechnology and pharmaceutical industries, national governments and international agencies. This situation gives rise to new types of organisations functioning as platforms for networking, debate and joint action among relevant actors. Examining the circumstances in which these organisations emerge, as well as their effects on research practices and regulatory structures, illuminates important aspects of governance in contemporary biomedical research and its effects on knowledge production. This is a case where, in the words of Andrew Barry (2001), the space of governance is being reconfigured, largely as a consequence of adopting new technologies for the production and exchange of data. In this chapter, I focus on the case of genomic consortia. These are self-organised
committees gathering specialists from various scientific fields to negotiate common standards for data dissemination, often with substantial consequences for the regulation of data sharing on a global scale. In particular, I discuss the case of bio-ontology consortia, organisations created to develop and maintain a labelling system for the distribution of data across research contexts. Bio-ontology consortia function as a muchneeded interface between bottom-up regulations arising from scientific practice, and top-down regulations produced by governmental and international agencies. They achieve this by focusing on practical problems encountered by researchers who use bioinformatic tools such as databases. A good example is the problem of data classification: that is, the tension that is bound to exist between the stability imposed by classificatory categories used in databases and the dynamism and diversity characterising the scientific practices through which data are produced. Bio-ontology consortia provide an institutional solution to the problem, by setting up mechanisms to select and update the labels given to data so as to mirror the expectations and needs of data users.
