Advancing University Career Paths in Interdisciplinary Data-Intensive Science

Sunday, 15 February 2015: 1:30 PM-4:30 PM
Room LL21F (San Jose Convention Center)
Extraordinary advances in our ability to acquire and generate data in the physical, biological, and social sciences are transforming the fundamental nature of discovery across domains. Extracting knowledge from this abundance of data -- data-intensive scientific discovery, or data science -- lies at the heart of 21st century discovery. This regime relies on developing a new intellectual research infrastructure at an institutional level: new career paths, new interdisciplinary education programs, and new methods and tools to empower researchers to pursue data-intensive discoveries. In the context of a new multi-institution partnership, this session describes progress to create and sustain: first, long-term career trajectories for a new generation of scientists whose research depends crucially on the analysis of massive, noisy, and/or complex data, and for the new breed of specialists in data science techniques; second, new educational programs that emphasize collaborations between domain researchers in the life, physical, and social sciences and methods researchers in computer science, statistics, and applied math; and, third, new methods and tools empowering researchers across scientific fields to make fundamental new discoveries. This session brings together experts, spanning three institutions and a number of different fields and approaches, working in data-intensive science and advancing new programs in data science at their home institutions.
William Howe, University of Washington
Cecilia Aragon, University of Washington
Cecilia Aragon, University of Washington
Future Career Paths for Data Scientists in Academia
Joshua Bloom, University of California
Computational and Data Literacy for Domain Scientists
Fernando Perez, University of California
IPython: From Interactive Computing to Computational Narratives
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