The world’s growing interest in data science is undeniable. One can see this reflected in the increased number of new academic degree and certificate programs, the number of new jobs available for individuals with data science skills, and the rising migration of researchers with computational skills to the private sector. In an effort to channel our efforts, we focus on five major themes around which academic data science discussions coalesce.

Data Science Education and Career Paths

Group Chairs: Tyler McCormick and Sarah Stone

This group develops innovative teaching methods and formats to make both formal and informal training in data science skills more accessible within and beyond the UW. We also focus on how to create and sustain long-term career trajectories for a new generation of researchers whose work depends crucially on the analysis of massive, noisy, and/or complex data.

Learn more about Data Science Education and Career Paths

Reproducible Science and Open Source Software

Group Chair: Ben Marwick

This group aims to promote the alignment of scientific ideals with research behaviors in the UW community. We fulfill this aim by sharing information, facilitating training and development – especially about open source scientific software – and working to implement sustainable campus policies to support transparency, open sharing, and reproducibility.

Learn more about Reproducible Science and Open Source Software

Members of the Data Science Studies Working Group meet

Data Science Studies

Group Chairs: Anissa Tanweer & Cecilia Aragon

UW Data Science Studies is a group of cross-disciplinary researchers studying the sociocultural and organizational processes around the emerging practice of data science.

Learn more about Data Science Studies

Neuroinformatics

Group Chair: Ariel Rokem

The neuroinformatics special interest group at the University of Washington (UW) eScience Institute and the University of Washington Institute for Neuroengineering (UWIN) focuses on neuroinformatics methods and their role in understanding the brain.

Learn more about Neuroinformatics

Neurohackweek participants work on their laptops

Algorithmic Foundations for Data Science Institute (ADSI)

Group Chair: John Thickstun

Seek new algorithms and design principles that unify ideas and provide a common language for addressing contemporary data science challenges at this special interest group.

Learn more about ADSI

Find a list of previous Working Groups here: https://escience.washington.edu/working-groups/