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Data-Centric Biology

A Philosophical Study

Sabina Leonelli

Data-Centric Biology

Sabina Leonelli

288 pages | 8 halftones | 6 x 9 | © 2016
Paper $35.00 ISBN: 9780226416472 Published November 2016
Cloth $105.00 ISBN: 9780226416335 Published November 2016
E-book $10.00 to $35.00 About E-books ISBN: 9780226416502 Published November 2016
In recent decades, there has been a major shift in the way researchers process and understand scientific data. Digital access to data has revolutionized ways of doing science in the biological and biomedical fields, leading to a data-intensive approach to research that uses innovative methods to produce, store, distribute, and interpret huge amounts of data. In Data-Centric Biology, Sabina Leonelli probes the implications of these advancements and confronts the questions they pose. Are we witnessing the rise of an entirely new scientific epistemology? If so, how does that alter the way we study and understand life—including ourselves?

 Leonelli is the first scholar to use a study of contemporary data-intensive science to provide a philosophical analysis of the epistemology of data. In analyzing the rise, internal dynamics, and potential impact of data-centric biology, she draws on scholarship across diverse fields of science and the humanities—as well as her own original empirical material—to pinpoint the conditions under which digitally available data can further our understanding of life. Bridging the divide between historians, sociologists, and philosophers of science, Data-Centric Biology offers a nuanced account of an issue that is of fundamental importance to our understanding of contemporary scientific practices.
Part One: Data Journeys

1          Making Data Travel: Technology and Expertise
1.1       The Rise of Online Databases in Biology
1.2       Packaging Data for Travel
1.3       The Emerging Power of Database Curators
1.4       Data Journeys and Other Metaphors of Travel
2          Managing Data Journeys: Social Structures
2.1       The Institutionalization of Data Packaging
2.2       Centralization, Dissent, and Epistemic Diversity
2.3       Open Data as Global Commodities
2.4       Valuing Data
Part Two: Data-Centric Science

3          What Counts as Data?
3.1       Data in the Philosophy of Science
3.2       A Relational Framework
3.3       The Nonlocality of Data
3.4       Packaging and Modeling
4          What Counts as Experiment?
4.1       Capturing Embodied Knowledge
4.2       When Standards Are Not Enough
4.3       Distributed Reasoning in Data Journeys
4.4       Dreams of Automation and Replicability
5          What Counts as Theory?
5.1       Classifying Data for Travel
5.2       Bio-Ontologies as Classificatory Theories
5.3       The Epistemic Role of Classification
5.4       Features of Classificatory Theories
5.5       Theory in Data-Centric Science

Part Three: Implications for Biology and Philosophy

6          Researching Life in the Digital Age
6.1       Varieties of Data Integration, Different Ways to Understand Organisms
6.2       The Impact of Data Centrism: Dangers and Exclusions
6.3       The Novelty of Data Centrism: Opportunities and Future Developments
7          Handling Data to Produce Knowledge
7.1       Problematizing Context
7.2       From Contexts to Situations
7.3       Situating Data in the Digital Age

Review Quotes
Hans-J├Ârg Rheinberger, Max Planck Institute for the History of Science
“The first critical book-length study of data centrism in the life sciences and beyond, Data-Centric Biology sheds new and surprising light on the phenomenon of big data. Analytically competent, historically informed, sociologically sensitive, this book is a brilliant and successful demonstration of what bringing together philosophy, history, and social studies of science can achieve.”
Mike Fortun, Rensselaer Polytechnic Institute
“Going far beyond the epistemic concerns that preoccupy many philosophers, Data-Centric Biology brilliantly shows readers the practices that make data informative and meaningful, the biocurators who carefully attend to data’s forms, and the social, economic, and political resources on which our systems of Big Data Sciences depend. Leonelli is a leader in this area of scholarship, commanding a vast comprehensive knowledge of the historical, philosophical, and social studies of the life sciences and the data practices that sustain them.”

London Schl Econ/Political Science: Lakatos Award in Philosophy of Science

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