Save the date!
The third Translational Data Science Workshop will be held at NYU CUSP on Thursday, October 25 – Friday October 26.
The ubiquity of data science, and its potential impact on individuals, science, and society, requires researchers and practitioners to pay careful attention to the translational aspects of data science. Translational data science encompasses the convergence of disciplines for greater impact; shared learning across multiple application areas; consideration of data science not just as a one-way process from foundations to applications, but as interactive feedback loops across the full data science lifecycle; and, incorporation of the broader societal context.
Building upon the discussions started at the two previous NSF-funded workshops of translational data science (University of Chicago Center for Data Intensive Science, 2017, and Berkeley Institute for Data Science, November 2017), this workshop will focus on exploring the following themes, highlighting case studies for each:
- Challenges of Translational Data Science, including incentives for data scientists in and different stakeholders to mutually engage in translational activities, and organizational, technical, and cultural challenges.
- Responsible Data Science: exploring how foundational issues in responsible use of data can be translated to data science practice, with a focus on public sector use cases.
- Open Questions: examining how translation fundamentally changes how data science is done, and what research problems (applied or basic) arise in this context.
(Updated October 24, 2018)
René Bastón, Northeast Big Data Innovation Hub
Juliana Freire, New York University
Chaitan Baru, UC San Diego
Meredith Lee, West Big Data Innovation Hub
Amen Ra Mashariki, ESRI
Katie Naum, Northeast Big Data Innovation Hub
Julia Stoyanovich, New York University
Elena Zheleva, University of Illinois at Chicago
NYU Center for Urban Science + Progress
370 Jay Street, Room 1201
Brooklyn, NY 11201
Participants are encouraged to book their hotel and travel directly. Funding is available to support travel costs; contact email@example.com for more information.