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Data-Centric Biology Vital Source e-bog
Sabina Leonelli
(2016)
University of Chicago Press
443,00 kr.
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Data-Centric Biology
A Philosophical Study
Sabina Leonelli
(2016)
Sprog: Engelsk
University of Chicago Press
399,00 kr.
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Detaljer om varen
- 1. Udgave
- Vital Source searchable e-book (Reflowable pages)
- Udgiver: University of Chicago Press (November 2016)
- ISBN: 9780226416502
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.
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Bookshelf online: 5 år fra købsdato.
Bookshelf appen: ubegrænset dage fra købsdato.
Udgiveren oplyser at følgende begrænsninger er gældende for dette produkt:
Print: 60 sider kan printes ad gangen
Copy: højest 50 sider i alt kan kopieres (copy/paste)
Detaljer om varen
- Paperback: 288 sider
- Udgiver: University of Chicago Press (November 2016)
- ISBN: 9780226416472
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.
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.
Introduction
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 Conclusion Acknowledgments Notes Bibliography Index
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 Conclusion Acknowledgments Notes Bibliography Index
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