The Making of “Fungible Open Data” in Biomedical Research: Regimes of Governance, Epistemic Trust, and Public Good

This talk discusses the epistemic, societal, and ethical implications of making publicly available and reusing open data from biomedical research. Today, making scientific data open is promoted by funding agencies and lawmakers as means to speed up the research process, leverage public investments in large-scale data collections, and increase public trust in science. Especially in genomics research, scientists are increasingly encouraged, and sometimes required, to make their data openly available right after data collection and prior to publication. These policies are challenging well-established community norms, scientific collaborative practices, and epistemic processes for knowledge validation. Moreover, scientists are concerned about the possibility for third parties to exploit their data inappropriately, unethically, or in misleading ways. The main case study is the FaceBase Consortium, a consortium for data sharing operating in the craniofacial research domain. Data types include facial images, metrics for facial norms, gene expression data, and results from genome-wide association studies (GWAS). The reuse of these various “kinds” of data has applications beyond their original context of production that span from the design of mobile apps for facial recognition to the development of forensic DNA phenotypic technologies.

Speaker Details

Irene Pasquetto is a Ph.D. Candidate in the Department of Information Studies at UCLA. Irene is a research assistant at the UCLA Center for Knowledge Infrastructures and also at the Participation Lab (PartLab) in the UCLA Institute for Society and Genetics. She teaches and co-teaches classes on data management, information ethics, and data economies. Her overarching research interest lies in the critical analysis of data-centric and computational technologies and epistemologies, especially in relation to their impact on policy-making and societal issues. For her dissertation research, Irene investigated the epistemic, socio-technical, and ethical challenges related to the open circulation of scientific knowledge, in the forms of data and software. She has also published on issues of genetic ancestry testing, data, and race, on police officer-involved homicide data evaluated through the theoretical lenses of critical data studies, and on the challenges of archiving and reusing climate-change data. With her work, Irene aims at informing the design and implementation of governance models for data and code infrastructures.