DEADLINE EXTENSION: 22 February 2019
Call for Participation - CHI 2019 Workshop:
Human-Centered Study of Data Science Work Practices
WS15, Saturday 4 May 2019, Glasgow, Scotland, UK
How should we study data science practices?
The creation and use of datasets, data science and machine learning
artifacts is a critical contemporary force on human cultures.
Bring your research perspective to an interdisciplinary workshop among
researchers from HCI, sociology, psychology, computer science, machine
learning and more.
Call for Participation
We hope to gather the growing community of researchers and practitioners in
HCI and allied fields who are building new insights, methods, and
collaborative practices around data science. Topics of interest include
(but are not limited to):
- Contextualize and understand data science work practices - by
individuals, and by groups and teams
- Characterize the work practices of data science workers, including
programming, ideation, and collaboration
- Building tools or methods to support human activities in data science work
- Show how practices of data creation and aggregation work of data science
- Understand the shared and unique design challenges of data science
environments, including methods and tools for comprehending data, data
wrangling, model building, debugging, collaborating and communicating
results, especially to non-programmers
- Support the incorporation of diverse ethics and human values into data
science work, e.g., in relation to algorithmic fairness or bias reduction.
- Bring sociotechnical and organizational perspectives on data work to bear
on data science education and practice
- Suggest methods of standardizing or coordinating data collection across
organizational and industry boundaries.
- Bridge the gap between the knowledge of data scientists and that of
domain experts in various fields of application
- Widen the audience for data science beyond highly technically skilled
programmers, to include UX designers, project managers, novice programmers,
and other stakeholders into a data-driven project
- Help policymakers to build more effective, appropriate, and transparent
rules around the complex domains of data science work
Important Dates
UPDATE> Paper submission deadline: February 22, 2019 (11:59 pm EST)
Notification of acceptance: March 1, 2019
UPDATE> Workshop at CHI in Glasgow: Saturday May 4, 2019
Details are at the workshop website: https://husdatworkshop.github.io/
Applications are open! Please email your submissions directly to
[log in to unmask]
Organizers: Michael Muller (IBM Research), Melanie Feinberg (University of
North Carolina), Timothy George (Project Jupyter), Steven Jackson (Cornell
University), Bonnie E. John (Bloomberg), Mary Beth Kery (Carnegie Mellon
University), and Samir Passi (Cornell University),
Primary contact: Michael Muller, [log in to unmask]
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Michael Muller, PhD, IBM Research, Cambridge MA USA
ACM Distinguished Scientist
ACM SIGCHI Academy
IBM Master Inventor
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