Datafied knowledge production
Introduction to the special theme
Bibliographic Data
| ID | 5260930 |
|---|---|
| Authors | Nanna Bonde Thylstrup (0000-0001-6094-2970, Copenhagen Business School, corresponding author), Mikkel Flyverbom (0000-0001-9465-6219, Copenhagen Business School), Rasmus Helles (0000-0002-1746-4755, University of Copenhagen) |
| Year | 2019 |
| Volume | 6 |
| Issue | 2 |
| Pages | 205395171987598 |
| Publication date | 2019-07-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Big Data & Society (JOURNAL) |
| Journal identifiers | ISSN: 2053-9517 • E-ISSN: 2053-9517 |
| Publisher | SAGE Publications Inc (PUBLISHER) |
| DOI | 10.1177/2053951719875985 |
| OpenAlex | W2976530716 |
| Language | EN |
| Citations received | 15 |
| References cited | 15 |
Framing datafication as new form of knowledge production has become a trope in both academic and commercial contexts. This special theme examines and ultimately rejects the familiar grand claims of datafication, to instead pay attention to emergent conversations that seek to take a more nuanced stock of the status and nature of datafied knowledge production. The articles in this special theme thus engage with datafied knowledge production through elaborate explorations of how datafied knowledge depends on the contexts of its production and the forms of knowledge production that precede it in those contexts. Our basic argument is that while the resources, material features and analytical operations involved in datafied knowledge production may be different, many fundamental concerns about epistemology, ontology and methods remain relevant to understand what shapes it. We still need to understand and explicate the assumptions, operations and consequences of emergent forms of knowledge production. If datafied knowledge production is neither a clean revolutionary break with past forms of knowledge production nor a balloon of pure hype, the articles in this special theme ask: what does the phenomenon of datafied knowledge production look like? Which digital and datafied infrastructures support its future development? And what potentialities and limits do such forms of analysis and knowledge production contain
Descriptive knowledge · Epistemology · Knowledge base · Knowledge management · Knowledge production · Ontology · Phenomenon · Sociology · Computer Science · Ethics and Social Impacts of AI · History · Information Systems Theories and Implementation · Mobile Crowdsensing and Crowdsourcing · Philosophy
Intersections Between Fintech Imaginaries and Traditional Banking
Absent Data
Datafying Museum Visitors
Measured Education
Prediction and data curation in digital humanitarianism
Claiming Universal Epistemic Authority – Relational Boundary Work and the Academic Institutionalization of Data Science
“We Need to Think about Their Real Needs”
Knowledge infrastructure crisis
Pay to play? Subverting the digital economy of Pokémon Go in the smart city
From ‘making lists’ to conducting ‘well-rounded’ studies
Building truths in AI
Dataficação da vida
Una mirada Ecopolítica al monitoreo ambiental comunitario en la Amazonía Colombiana Caqueteña
Scraping the demos. Digitalization, web scraping and the democratic project
New media and cultural heritage politics
A Narrative Approach to Organization Studies
Neither Black Nor Box
Steps Toward an Ecology of Infrastructure
Sorting Things Out
On Nonscalability
Meshes of Surveillance, Prediction, and Infrastructure
Computing the everyday
Hydraulic City
Critical Questions for Big Data
Beyond opening up the black box
Algorithms as culture
The politics of large numbers
| Unique citing works | 15 |
|---|---|
| Citations per year | 2,5 |
| Citation span | 2020 - 2025 (6) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 10 |