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Professor Sabina Leonelli
Professor of Philosophy and History of Science, University of Exeter
CV
SABINA LEONELLI is Professor of Philosophy and History of Science at the University of Exeter, UK. She serves as the Co-Director of the Exeter Centre for the Study of the Life Sciences where she leads the Data Studies research strand, and is a member of the Open Science Policy Platform of the European Commission, representing the Global Young Academy. She is also a key expert for the Mutual Learning Exercise on Open Science of the European Commission.
Her research focuses on the philosophy, history and sociology of data-intensive science, especially the methods, sharing tools and outputs involved in the production, dissemination and use of open and big data. She is interested in how big data and open science are redefining what counts as research and knowledge, and particularly how this affects low-resourced research environments.
Until 2019 she holds a European Research Council grant to investigate and compare existing strategies for dissemination and re-use of data across several fields, with emphasis on the biological and biomedical domains; and is co-investigator on a Discovery Award by the Australian Research Council, studying the use of living organisms as models and data sources for research in the life sciences. She published over sixty papers in high-ranking peer-reviewed journals within biology as well as the philosophy, social studies and history of science, and is the author of Data-Centric Biology: A Philosophical Study (2016, Chicago University Press).
Abstract
Abstract:Using Big and Open Data to Benefit Humanity
The rise of Big Data (and related infrastructures and expertise) is intertwined with the rise of Open Science, a movement that takes advantage of digital platforms and communication technologies to revolutionise how knowledge is created, disseminated and evaluated around the globe. The juncture of Big and Open Data is informing areas as diverse as artificial intelligence, agriculture and public health, and promises to transform human abilities to tackle global challenges. At the same time, however, it also has the potential to profoundly undermine the legitimacy, credibility and trustworthiness of scientific expertise, and further expand the already overwhelming divide between those who benefit from digital technologies and those who are losing out.
Building on research on how data are shared and re-used across and beyond scientific research fields, I identify three major concerns associated to the ways in which Big and Open Data are currently managed. The first is the extent to which they are reinforcing existing social divides, for instance by favoring data sources that represent only privileged individuals and communities. The second is the quality and credibility of the data themselves and the processes used to produce knowledge, and the lack of accountability built into the highly distributed networks through which data are disseminated. The third is the unsustainable nature of the digital data landscape, given the costs associated with maintaining and updating data infrastructures and the lack of clarity around who is responsible for shouldering those costs in the long term.
These challenges can be overcome through substantial investment in data governance, which should aim to support
- fairness in data handling through the identification of exclusions and inequalities built into data pipelines
- the development of adequate data expertise and the understanding that whether and how data should be open needs to be decided on a case-by-case basis;
- mechanisms to promote the quality and trustworthiness of data sources and analytic tools;
- sustainable data infrastructures (and related expertise), that is resources that are interoperable, long-term, internationally coordinated and publicly accountable;
- creative solutions to global challenges in dialogue with relevant publics; and
- critical scrutiny of research across different audiences.