Introduction .................................................... I
Part One: Data Journeys
1 Making Data Travel: Technology and Expertise ................ 13
1.1 The Rise of Online Databases in Biology ................ 17
1.2 Packaging Data for Travel .............................. 24
1.3 The Emerging Power of Database Curators ................ 31
1.4 Data Journeys and Other Metaphors of Travel ............ 38
2 Managing Data Journeys: Social Structures ................... 45
2.1 The Institutionalization of Data Packaging ............. 46
2.2 Centralization, Dissent, and Epistemic Diversity ....... 52
2.3 Open Data as Global Commodities ........................ 56
2.4 Valuing Data ........................................... 63
Part Two: Data-Centric Science
3 What Counts as Data? ........................................ 69
3.1 Data in the Philosophy of Science ...................... 71
3.2 A Relational Framework ................................. 77
3.3 The Nonlocality of Data ................................ 84
3.4 Packaging and Modeling ................................. 88
4 What Counts дs Experiment? .................................. 93
4.1 Capturing Embodied Knowledge ........................... 95
4.2 When Standards Are Not Enough ......................... 100
4.3 Distributed Reasoning in Data Journeys ................ 106
4.4 Dreams of Automation and RepLicabiLity ................ 111
5 What Counts as Theory? ..................................... 114
5.1 Classifying Data for Travel ........................... 115
5.2 Bio-Ontologies as Classificatory Theories ............. 121
5.3 The Epistemic Role of Classification .................. 127
5.4 Features of Classificatory Theories ................... 130
5.5 Theory in Data-Centric Science ........................ 135
Part Three: Implications for Biology and Philosophy
6 Researching Life in the Digital Age ........................ 141
6.1 Varieties of Data Integration, Different Ways to
Understand Organisms .................................. 143
6.2 The Impact of Data Centrism: Dangers and Exclusions ... 160
6.3 The Novelty of Data Centrism: Opportunities and
Future Developments ................................... 169
7 Handling Data to Produce Knowledge ......................... 176
7.1 Problematizing Context ................................ 179
7.2 From Contexts to Situations ........................... 181
7.3 Situating Data in the Digital Age ..................... 186
Conclusion ................................................. 193
Acknowledgments ............................................ 199
Notes ...................................................... 203
Bibliography ............................................... 237
Index ...................................................... 263
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