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How Domain Experts Work with Data: Situating Data Science in the Practices and Settings of Craftwork
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/asi.23563openalex-snapshot
Data science on the ground: Hype, criticism, and everyday work
inferredcites →https://doi.org/10.1002/j.2050-0416.2011.tb00480.xopenalex-snapshot
Comparing the Impact of Environmental Factors During Very High Gravity Brewing Fermentations
inferredcites →https://doi.org/10.1007/978-3-319-59536-8_5openalex-snapshot
Development of Mobile Data Collection Applications by Domain Experts: Experimental Results from a Usability Study
inferredcites →https://doi.org/10.1007/978-3-540-28645-5_29openalex-snapshot
Learning with Drift Detection
inferredcites →https://doi.org/10.1007/s10606-006-9023-2openalex-snapshot
Enriching the Notion of Data Curation in E-Science: Data Managing and Information Infrastructuring in the Long Term Ecological Research (LTER) Network
inferredcites →https://doi.org/10.1007/s10606-009-9096-9openalex-snapshot
Software Development Cultures and Cooperation Problems: A Field Study of the Early Stages of Development of Software for a Scientific Community
inferredcites →https://doi.org/10.1007/s10606-012-9169-zopenalex-snapshot
Who’s Got the Data? Interdependencies in Science and Technology Collaborations
inferredcites →https://doi.org/10.1007/s10606-012-9183-1openalex-snapshot
Reflections on 25 Years of Ethnography in CSCW
inferredcites →https://doi.org/10.1007/s10606-012-9184-0openalex-snapshot
Supporting Scientific Collaboration: Methods, Tools and Concepts
inferredcites →https://doi.org/10.1007/s10606-017-9279-8openalex-snapshot
Paper Practices in Institutional Talk: How Financial Advisors Impress their Clients
inferredcites →https://doi.org/10.1016/0141-0229(85)90134-6openalex-snapshot
The biotechnology of malting and brewing
inferredcites →https://doi.org/10.1016/j.compchemeng.2020.106881openalex-snapshot
Considerations, challenges and opportunities when developing data-driven models for process manufacturing systems
inferredcites →https://doi.org/10.1016/j.ijhcs.2020.102562openalex-snapshot
Talking datasets – Understanding data sensemaking behaviours
inferredcites →https://doi.org/10.1017/cbo9780511625510.006openalex-snapshot
Thinking and acting with iron
inferredcites →https://doi.org/10.1023/a:1008713826637openalex-snapshot
Tailoring as Collaboration: The Mediating Role of Multiple Representations and Application Units
inferredcites →https://doi.org/10.1080/01972243.2011.583819openalex-snapshot
Critical Making: Conceptual and Material Studies in Technology and Social Life
inferredcites →https://doi.org/10.1080/87559129.2020.1753207openalex-snapshot
Crafty Marketing: An Evaluation of Distinctive Criteria for “Craft” Beer
inferredcites →https://doi.org/10.1086/341840openalex-snapshot
Predictive Accuracy as an Achievable Goal of Science
inferredcites →https://doi.org/10.1093/jdh/11.1.102openalex-snapshot
Abstracting Craft: The Practiced Digital Hand
inferredcites →https://doi.org/10.1093/oso/9780198862536.003.0019openalex-snapshot
Human–Machine Collaboration for Democratizing Data Science
inferredcites →https://doi.org/10.1109/mitp.2013.93openalex-snapshot
Data Scientists Aren't Domain Experts
inferredcites →https://doi.org/10.1109/ms.2009.134openalex-snapshot
Metadesign: Guidelines for Supporting Domain Experts in Software Development
inferredcites →https://doi.org/10.1109/tvcg.2019.2934593openalex-snapshot
Understanding the Role of Alternatives in Data Analysis Practices
inferredcites →https://doi.org/10.1111/j.1467-954x.1984.tb00108.xopenalex-snapshot
The Values of Quantification
inferredcites →https://doi.org/10.1145/1553374.1553378openalex-snapshot
Incorporating domain knowledge into topic modeling via Dirichlet Forest priors
inferredcites →https://doi.org/10.1145/1958824.1958904openalex-snapshot
Scientific software production
inferredcites →https://doi.org/10.1145/1961189.1961191openalex-snapshot
Prediction in financial markets
inferredcites →https://doi.org/10.1145/2145204.2145375openalex-snapshot
The material practices of collaboration
inferredcites →https://doi.org/10.1145/240080.240342openalex-snapshot
Documents and professional practice
inferredcites →https://doi.org/10.1145/2531602.2531614openalex-snapshot
"it's in your spinal cord, it's in your fingertips"
inferredcites →https://doi.org/10.1145/2639189.2639194openalex-snapshot
Reflections on craft research for and through design
inferredcites →https://doi.org/10.1145/2858036.2858363openalex-snapshot
Everyday Food Science as a Design Space for Community Literacy and Habitual Sustainable Practice
inferredcites →https://doi.org/10.1145/2998181.2998265openalex-snapshot
Characteristics of Collaboration in the Emerging Practice of Open Data Analysis
inferredcites →https://doi.org/10.1145/3025453.3025738openalex-snapshot
How Data Workers Cope with Uncertainty
inferredcites →https://doi.org/10.1145/3173574openalex-snapshot
Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems
inferredcites →https://doi.org/10.1145/3287560.3287567openalex-snapshot
Problem Formulation and Fairness
inferredcites →https://doi.org/10.1145/3290605.3300233openalex-snapshot
Guidelines for Human-AI Interaction
inferredcites →https://doi.org/10.1145/3290605.3300322openalex-snapshot
Towards Effective Foraging by Data Scientists to Find Past Analysis Choices
inferredcites →https://doi.org/10.1145/3290605.3300356openalex-snapshot
How Data Science Workers Work with Data
inferredcites →https://doi.org/10.1145/3290607.3299018openalex-snapshot
Human-Centered Study of Data Science Work Practices
inferredcites →https://doi.org/10.1145/3290607.3299032openalex-snapshot
Computational Modeling in Human-Computer Interaction
inferredcites →https://doi.org/10.1145/3301275.3302324openalex-snapshot
Towards human-guided machine learning
inferredcites →https://doi.org/10.1145/3313831.3376177openalex-snapshot
Understanding and Visualizing Data Iteration in Machine Learning
inferredcites →https://doi.org/10.1145/3313831.3376216openalex-snapshot
Officers Never Type: Examining the Persistence of Paper in e-Governance
inferredcites →https://doi.org/10.1145/3313831.3376219openalex-snapshot
Interpreting Interpretability: Understanding Data Scientists' Use of Interpretability Tools for Machine Learning
inferredcites →https://doi.org/10.1145/3325480.3325487openalex-snapshot
Crafting in a Community of Practice
inferredcites →https://doi.org/10.1145/3334480.3382845openalex-snapshot
How Domain Experts Structure Their Exploratory Data Analysis: Towards a Machine-Learned Storyline
inferredcites →https://doi.org/10.1145/3359141openalex-snapshot
How Data Scientists Use Computational Notebooks for Real-Time Collaboration
inferredcites →https://doi.org/10.1145/3359313openalex-snapshot
Human-AI Collaboration in Data Science
inferredcites →https://doi.org/10.1145/3361118openalex-snapshot
How Data ScientistsWork Together With Domain Experts in Scientific Collaborations
inferredcites →https://doi.org/10.1145/3392826openalex-snapshot
How do Data Science Workers Collaborate? Roles, Workflows, and Tools
inferredcites →https://doi.org/10.1145/3397481.3450637openalex-snapshot
Facilitating Knowledge Sharing from Domain Experts to Data Scientists for Building NLP Models
inferredcites →https://doi.org/10.1145/3411764.3445306openalex-snapshot
Whither AutoML? Understanding the Role of Automation in Machine Learning Workflows
inferredcites →https://doi.org/10.1145/3411764.3445518openalex-snapshot
“Everyone wants to do the model work, not the data work”: Data Cascades in High-Stakes AI
inferredcites →https://doi.org/10.1145/3419249.3420152openalex-snapshot
Co-designing Data Experiments
inferredcites →https://doi.org/10.1145/3449205openalex-snapshot
How AI Developers Overcome Communication Challenges in a Multidisciplinary Team
inferredcites →https://doi.org/10.1145/357442.357445openalex-snapshot
Office procedure as practical action
inferredcites →https://doi.org/10.1145/637069openalex-snapshot
Proceedings of the 1986 ACM conference on Computer-supported cooperative work - CSCW '86
inferredcites →https://doi.org/10.1177/0894439318788314openalex-snapshot
Artificial Intelligence and Inclusion: Formerly Gang-Involved Youth as Domain Experts for Analyzing Unstructured Twitter Data
inferredcites →https://doi.org/10.1177/0920203x14529881openalex-snapshot
Hackerspaces and the Internet of Things in China: How makers are reinventing industrial production, innovation, and the self
inferredcites →https://doi.org/10.1177/0964663907079762openalex-snapshot
Toward a Theorization of Craft
inferredcites →https://doi.org/10.1177/2053951714528481openalex-snapshot
Big Data, new epistemologies and paradigm shifts
inferredcites →https://doi.org/10.1207/s15327051hci1523_5openalex-snapshot
The Intellectual Challenge of CSCW: The Gap Between Social Requirements and Technical Feasibility
inferredcites →https://doi.org/10.1609/aimag.v35i4.2513openalex-snapshot
Power to the People: The Role of Humans in Interactive Machine Learning
inferredcites →https://doi.org/10.2307/2655659openalex-snapshot
Talking about Machines: An Ethnography of a Modern Job
inferredcites →https://doi.org/10.3390/beverages5020033openalex-snapshot
Development of Artificial Neural Network Models to Assess Beer Acceptability Based on Sensory Properties Using a Robotic Pourer: A Comparative Model Approach to Achieve an Artificial Intelligence System
inferredcites →https://doi.org/10.3390/beverages5020038openalex-snapshot
Computer Vision Method in Beer Quality Evaluation—A Review
inferredcites →https://doi.org/10.5860/choice.36-0976openalex-snapshot
Beer: tap into the art and science of brewing
inferredcites →https://doi.org/10.7551/mitpress/4833.001.0001openalex-snapshot
The Myth of the Paperless Office
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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How Engineers Perform Data Science Work: Designing Hybrid Roles
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inferred← citeshttps://doi.org/10.1109/tvcg.2025.3634821openalex-snapshot
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inferred← citeshttps://doi.org/10.1145/3544549.3577062openalex-snapshot
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inferred← citeshttps://doi.org/10.1145/3579607openalex-snapshot
From Bias to Repair: Error as a Site of Collaboration and Negotiation in Applied Data Science Work
inferred← citeshttps://doi.org/10.1145/3584931.3607020openalex-snapshot
NBGuru: Generating Explorable Data Science Flowcharts to Facilitate Asynchronous Communication in Interdisciplinary Data Science Teams
inferred← citeshttps://doi.org/10.1145/3613905.3651115openalex-snapshot
Leveraging Large Language Models to Enhance Domain Expert Inclusion in Data Science Workflows
inferred← citeshttps://doi.org/10.1145/3637317openalex-snapshot
Data Work Between the Local and the Global: An Ethnography of a Healthcare Business Intelligence Unit
inferred← citeshttps://doi.org/10.1145/3686904openalex-snapshot
"Guilds" as Worker Empowerment and Control in a Chinese Data Work Platform
inferred← citeshttps://doi.org/10.1145/3687009openalex-snapshot
"Come to us first": Centering Community Organizations in Artificial Intelligence for Social Good Partnerships
inferred← citeshttps://doi.org/10.1145/3706598.3713112openalex-snapshot
The Making of Performative Accuracy in AI Training: Precision Labor and Its Consequences
inferred← citeshttps://doi.org/10.1145/3706598.3713497openalex-snapshot
Explanatory Debiasing: Involving Domain Experts in the Data Generation Process to Mitigate Representation Bias in AI Systems
inferred← citeshttps://doi.org/10.1145/3706598.3713621openalex-snapshot
Understanding Marine Scientist Software Tool Use
inferred← citeshttps://doi.org/10.1145/3706598.3713913openalex-snapshot
Jupybara: Operationalizing a Design Space for Actionable Data Analysis and Storytelling with LLMs
inferred← citeshttps://doi.org/10.1145/3706598.3714051openalex-snapshot
PromptHive: Bringing Subject Matter Experts Back to the Forefront with Collaborative Prompt Engineering for Educational Content Creation
inferred← citeshttps://doi.org/10.1145/3708319.3734171openalex-snapshot
Building Human-AI Reliance Through Cognitive Engagement and Exploratory AI Assistance
inferred← citeshttps://doi.org/10.1145/3772363.3799192openalex-snapshot
Understanding and Designing Human-Centered AI Interactions for Non-Expert Users
inferred← citeshttps://doi.org/10.1177/18333583231183083openalex-snapshot
Digital health care and data work: Who are the data professionals?
inferred← citeshttps://doi.org/10.31219/osf.io/dn32zopenalex-snapshot
Here’s what you need to know about my data: Exploring Expert Knowledge’s Role in Data Analysis.
inferred← citeshttps://doi.org/10.38159/ehass.202451111openalex-snapshot
The Role of Collaboration and Networking in the Digital Age: Students’ Perspectives
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