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Data and Society: A Critical Introduction investigates the growing importance of data as a technological, social, economic and scientific resource. It explains how data practices have come to underpin all aspects of human life and explores what this means for those directly involved in handling data.
The book
- fosters informed debate over the role of data in contemporary society
- explains the significance of data as evidence beyond the "Big Data" hype
- spans the technical, sociological, philosophical and ethical dimensions of data
- provides guidance on how to use data responsibly
- includes data stories that provide concrete cases and discussion questions.
Grounded in examples spanning genetics, sport and digital innovation, this book fosters insight into the deep interrelations between technical, social and ethical aspects of data work.
List of contents
Section 1: Data in Society
Chapter 1: Data in Society
Section 2: Data Creation
Chapter 2: Big Data in Context
Chapter 3: Characteristics of Data
Chapter 4: Data, Evidence and Knowledge
Section 3: Data Circulation
Chapter 5: Putting Data to Work
Chapter 6: New Data Skills
Chapter 7: Governance of Data Journeys
Section 4: Data Value, Innovation and Responsibility
Chapter 8: Data as a Source of Value
Chapter 9: Data Justice and Ethics
Chapter 10: Responsible Use of Data as Evidence
Section 5: Conclusion: Data and the Knowledge We Need
Chapter 11: Towards Good Data Science
About the author
Anne Beaulieu is Associate Professor of Science and Technology Studies and director of the Data Research Centre, University of Groningen. She leads the research group Knowledge Infrastructures for Sustainability at Campus Fryslân and developed the minor Data Wise: Data Science in Society (with Gert Stulp). Beaulieu’s research focuses on diversity and complexity in knowledge infrastructures, with particular attention to digital data assemblages and interfaces for the creation and circulation of knowledge. She is co-author of Virtual Knowledge: Experimenting in the Humanities and Social Sciences and has published widely on the significance of ethnographic methods for the study of data practices. Beaulieu was visiting research fellow at the Pufendorf Institute for Advance Studies, Lund University, Sweden (2017-18) and visiting professor at the STS Department of the University of Vienna, Austria (2018). Since September 2018, she is co-coordinator of the PhD training network of the Netherlands Graduate Research School of Science, Technology and Modern Culture (WTMC), and has developed numerous innovative courses in the major Responsible Planet at University College Fryslân.Sabina Leonelli is Professor in Philosophy and History of Science at the University of Exeter, where she co-directs the Centre for the Study of the Life Sciences and leads the governance strand of the Institute for Data Science and Artificial Intelligence. Her interdisciplinary research and collaborations focus on the epistemology and governance of scientific data and models, and the role of open science in the global – and highly unequal - research landscape. She is Fellow of the Alan Turing Institute and the Académie Internationale de Philosophie de la Science; Editor-in-Chief of History and Philosophy of the Life Sciences; and Associate Editor of the Harvard Data Science Review. She served as expert advisor for national and international agencies and received funding from several public funders including two awards from the European Research Council. Her books include the award-winning Data-Centric Biology: A Philosophical Study (Chicago UP, 2016) and Data Journeys in the Sciences (Springer, 2020, with Niccolo Tempini).
Summary
The standard teaching text for Data and Society modules explaining to undergraduates, in different social-science disciplines, the Big Data Revolution in an accessible and critical way.
Report
As the Founding Editor-in-chief of Harvard Data Science Review, I have studied thousands of pages of data science, with or without Greek letters. But nothing has had a higher density of inspirations per page than Beaulieu and Leonelli s book. Without going beyond page 5, I already started to think about data singularly and plurally. Professor Xiao-Li Meng
