Data Cleaners for Pristine Datasets
Visibility and Invisibility of Data Processors in Social Science
Bibliographic Data
| ID | 5338023 |
|---|---|
| Authors | Jean-Christophe Plantin (0000-0001-8041-6679, London School of Economics and Political Science, corresponding author) |
| Year | 2019 |
| Volume | 44 |
| Issue | 1 |
| Pages | 52-73 |
| Publication date | 2019-01-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Science Technology & Human Values (JOURNAL) |
| Journal identifiers | ISSN: 0162-2439 • E-ISSN: 1552-8251 |
| Publisher | SAGE Publications Inc (PUBLISHER) |
| DOI | 10.1177/0162243918781268 |
| OpenAlex | W2808686972 |
| Language | EN |
| Citations received | 37 |
| References cited | 30 |
This article investigates the work of processors who curate and "clean" the data sets that researchers submit to data archives for archiving and further dissemination. Based on ethnographic fieldwork conducted at the data processing unit of a major US social science data archive, I investigate how these data processors work, under which status, and how they contribute to data sharing. This article presents two main results. First, it contributes to the study of invisible technicians in science by showing that the same procedures can make technical work invisible outside and visible inside the archive, to allow peer review and quality control. Second, this article contributes to the social study of scientific data sharing, by showing that the organization of data processing directly stems from the conception that the archive promotes of a valid data set-that is, a data set that must look "pristine" at the end of its processing. After critically interrogating this notion of pristineness, I show how it perpetuates a misleading conception of data as "raw" instead of acknowledging the important contribution of data processors to data sharing and social science
Data Processing · Data quality · Data science · Data set · Data sharing · Database · Ethnography · Geography · Invisibility · Raw data · Sociology · Visibility · World Wide Web · Computer Science · Data Analysis and Archiving · Engineering · Ethics in Clinical Research · Research Data Management Practices · Artificial Intelligence
Labor Out of Place
Data Durabilities
Care and Scale
Critical Data Studies Meet Sociology
Collecting Lives
Maintenance and Care
Researchers and their data
Infrastructural hubris and platform power
Primer Sledilnik
The digital turn in planning and the production of ‘good enough’ planning systems
When Being a Data Annotator Was Not Yet a Job
Data centers and the infrastructural temporalities of digital media
The social construction of datasets
Qui prend soin des algorithmes ? Perspective féministe sur le travail invisible de l’IA
Care, collaboration, and service in academic data work
‘Place a book and walk away’
Algorithmic futures
Citizens’ data afterlives
The “Unsung Heroes” of the “Infocalypse
Platforms, programmability, and precarity
Databasing Violence
How permanent are metadata for research data? Understanding changes in DataCite metadata
Ground-truth is law
The cost of (data) community
Coordinative Entities
The ethics and politics of data sets in the age of machine learning
More Instrument than Data
Rediscovering the 1
Data mobilities
A Patchwork of Data Systems
Lifting the curtain
The data archive as factory
Producing and projecting data
Sensing and the Shadows
Controlling the Schengen Information System (SIS II)
Wikidata as Semantic Infrastructure
Checking Facts by a Bot
International Handbook of Internet Research
Big Data, Little Data, No Data
Data-Centric Biology
The Long Now of Technology Infrastructure
The TEA Set
Steps Toward an Ecology of Infrastructure
La politique des grands nombres
Studying the History of Social Science Data Archives as Knowledge Infrastructure
Survey Research in the United States
Laboratory Life
Sorting Things Out
The Rise of Statistical Thinking, 1820–1900
A Black Technician and Blue Babies
Technical Work and Critical Inquiry
Rawification and the careful generation of open government data
I.1 The Work of a Discovering Science Construed with Materials from the Optically Discovered Pulsar
Layers of Silence, Arenas of Voice
Critical Questions for Big Data
Re-integrating scholarly infrastructure
Standards
Les mains dans les bases de données
La science en réseau
Going Monoclonal
In the Backrooms of Science
| Unique citing works | 37 |
|---|---|
| Citations per year | 4,63 |
| Citation span | 2018 - 2026 (9) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 33 |