Scientific Remix
Epistemic Idioms and the Spread of Data Science
Bibliographic Data
| ID | 24237018 |
|---|---|
| Authors | Anissa Tanweer (0000-0002-8868-4288, University of Washington) |
| Year | 2026 |
| Pages | 3063127261489301-3063127261489301 |
| Publication date | 2026-10-20 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Social Studies of Science (JOURNAL) |
| Journal identifiers | ISSN: 0306-3127 • E-ISSN: 1460-3659 |
| Publisher | SAGE Publications (PUBLISHER • US) |
| DOI | 10.1177/03063127261489301 |
| PMID | 42902547 |
| OpenAlex | W7223144196 |
| Language | EN |
| References cited | 33 |
Scholarship on science has long contained a tension between accounts emphasizing convergent forces and those highlighting divergent practices. This article addresses that tension through an ethnographic study of data science. It advances the concept of epistemic idiom —a recognizable and portable pattern of practices that evolve alongside knowledge-making tools, analogous to musical idioms arising from the interaction of material affordances and learned techniques. Through analysis of a project attempting to sequence chromosomal centromeres, I show participants enacting the nomad idiom of data science: a data-led approach involving tools for iteration and exploration, cross-disciplinary borrowing, bricolage construction of bespoke assemblages, and the motivation to scale. Though the project failed to sequence centromeres, it generated unexpected discoveries, challenged established theories, and yielded lasting changes to scientific practice. The case reveals how epistemic trends can spread without being totalizing—the nomad idiom enabled both convergence (shared technical toolkit) and divergence (local adaptations, surprise outcomes) simultaneously. The epistemic idiom concept complements existing STS frameworks by explaining how practices can migrate across epistemic communities, while those communities retain distinct cultures. It speaks to concerns over computational universalism and epistemic monocultures, demonstrating that alternatives exist—ways for scientific trends to be borrowed rather than imposed, becoming remixes instead of replacements.
Interdisciplinary Research and Collaboration · Philosophy and History of Science · Scientific Computing and Data Management
Networking Peripheries
Inventing Temperature
Never Pure
Artificial intelligence and illusions of understanding in scientific research
Falsification and the Methodology of Scientific Research Programmes
Trust in Numbers
The Structure of Scientific Revolutions
The logic of domains
Computational universalism, or, Attending to relationalities at scale
Academic data science
Epistemic Cultures in Conflict
Sociology in the Era of Big Data
Discovering needs for digital capitalism
Adaptive Epistemologies
Ontologies, methodologies, and new uses of Big Data in the social and cultural sciences
In defense of forensic social science
What difference does quantity make? On the epistemology of Big Data in biology
Prospecting (in) the data sciences
Epistemic Cultures
Data Scientists' Identity Work
Replace, absorb, serve
The gates to the profession are open
| Highly cited | No |
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