Translational Data Science Workshop

Translational data science is an emerging field that applies data science principles, techniques and technologies to scientific, economic, and societal challenges that hold the promise of having an important national impact. In order to understand the important shifts in how data is used and applied to many aspects of daily life, it is important to effectively apply these principles and tools within our diverse research environments to successfully address these challenges for the benefit of human and societal welfare. This workshop will build upon discussions initiated at two previous NSF-funded workshops on translational data science and focus on the challenges of engaging in translational data science; challenges related to technical issues; and challenges related to organizational and cultural change. The perspectives and insights shared from industry, government, nonprofits, and academia, coupled with discussions focused on actionable challenges and measurable outcomes, will serve to advance the field of data science as well as related fields and application areas. This workshop will provide mechanisms for identifying high-priority topics and high-impact opportunities for future research, training, and collaboration.

The objectives of this workshop will be to facilitate the growth of the emerging community related to translational data science; strengthen existing connections; and engage the academic community with the perspectives and insights available from industrial and public sector partners. Another objective will be to discuss and align different views about the challenges that are most important in translational data science, and clearly identify opportunities and high priority areas to guide research and funding. By convening a diverse community of stakeholders who can contribute to the strategic development of a translational data science roadmap and ecosystem, this workshop will build and strengthen connections across sectors. Another theme of the workshop will be 'responsible data science', to explore how foundational issues in responsible use of data can be translated to data science practice, with a focus here on public sector use cases. The workshop will also discuss open issues related to if and how the notion of translational data science fundamentally changes how data science is practiced and taught, and the applied and basic research and pedagogical issues that may arise in this context.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.