How Data Need People
The Social and Epistemic Practice of a Data-Rich Science
2026
Cambridge University Press (Verlag)
978-1-009-68672-3 (ISBN)
Cambridge University Press (Verlag)
978-1-009-68672-3 (ISBN)
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Taking an anthropological approach to data-rich science, this book examines the social interactions, relations, and accountabilities that shape how scientists and technicians make, use, publish, and reuse digital data. It is an essential reading for researchers, students, and others interested in data science and science and technology studies.
From genome sequencing to large sky surveys, digital technologies produce massive datasets that promise unprecedented scientific insights. But data, for being good to use and reuse, need people – scientists, technicians, and administrators – as embodied, evaluative, social humans. In this book, anthropologist Götz Hoeppe draws on an ethnography of astronomical research to examine the media and practices that scientists and technicians use to instruct graduate students, make diagrams for data calibration and discovery, organize collaborative work, negotiate the ethics of open access, encode their knowledge in datasets – and do social inquiries along the way. This book offers a reflection on the sociality of data-rich research that will benefit attempts to integrate human and machine learning. It is essential reading for anyone interested in data science, science and technology studies, as well as the anthropology, sociology, history, and philosophy of science. This book is also available Open Access on Cambridge Core.
From genome sequencing to large sky surveys, digital technologies produce massive datasets that promise unprecedented scientific insights. But data, for being good to use and reuse, need people – scientists, technicians, and administrators – as embodied, evaluative, social humans. In this book, anthropologist Götz Hoeppe draws on an ethnography of astronomical research to examine the media and practices that scientists and technicians use to instruct graduate students, make diagrams for data calibration and discovery, organize collaborative work, negotiate the ethics of open access, encode their knowledge in datasets – and do social inquiries along the way. This book offers a reflection on the sociality of data-rich research that will benefit attempts to integrate human and machine learning. It is essential reading for anyone interested in data science, science and technology studies, as well as the anthropology, sociology, history, and philosophy of science. This book is also available Open Access on Cambridge Core.
Preface; Acknowledgements; Introduction: making sense of data-centric socialities; 1. Medium: digital affordances; 2. Evaluations: the ethical life of data production; 3. Membership: learning to become a competent data user; 4. Diagrams: spaces for cultivating data and making discoveries; 5. World: mundane reason and the relief from trust in data makers; 6. Organizing: social, medial, and epistemic orders in data-centric collaboration; 7. Normativity: inhabiting statuses in 'Open Science'; 8. Encoding knowledge: how to make data speak for themselves; Outlook: scientific data, artificial intelligence, and people; Appendix: Transcription conventions; References; Index.
| Erscheint lt. Verlag | 30.6.2026 |
|---|---|
| Zusatzinfo | Worked examples or Exercises |
| Verlagsort | Cambridge |
| Sprache | englisch |
| Gewicht | 500 g |
| Themenwelt | Geisteswissenschaften ► Psychologie |
| Informatik ► Datenbanken ► Data Warehouse / Data Mining | |
| Sozialwissenschaften ► Ethnologie | |
| Sozialwissenschaften ► Soziologie | |
| ISBN-10 | 1-009-68672-0 / 1009686720 |
| ISBN-13 | 978-1-009-68672-3 / 9781009686723 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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