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.

Quantitative Cell Biology and Communities (QCBC)

Group Chairs: David Beck and Joseph Hellerstein

Rapid progress in the quality and quantity of laboratory data on cellular processes enable the development of quantitative models of cells and cell communities that can usher in a new era of materials, personal medicine, environmental remediation and more. We refer to this emerging area as Quantitative Cell Biology and Communities (QCBC). The QCBC special interest group at the eScience Institute focuses on data management, processing pipelines, and modeling, and machine learning methodologies for understanding the biology of cells, viruses, and their communities.

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

Text-as-Data

Group Chairs: Spencer Wood and John Wilkerson

Text is a ubiquitous and valued data source in the computer and information sciences, many areas of the natural and social sciences, engineering, business and more. This eScience Special Interest Group is for students, faculty and researchers interested in sharing and learning about UW research and teaching that uses text as data.

Learn more about the Text-as-Data Special Interest Group

A graphic that reads "text as data"

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
A satellite image depicting land and water

Satellite Image Analysis

Group Chairs: Valentina Staneva & Amanda Tan

This special interest group utilizes satellite imagery data sets provided by both federal institutions and private companies to answer questions in a variety of domains.

Learn more about Satellite Image Analysis

Computational Demography Working Group (CDWG)

Group Chairs: Connor Gilroy, Neal Marquez, Lee Fiorio, Tim Thomas, Sara Curran, Matt Dunbar, and Jon Wakefield

The CDWG discuss topics related to: demographic data and computational and statistical methods, share students & faculty tools, develop via demos or tutorials, and graduate student & faculty research workshops. This group is hosted jointly with the UW Center for Studies in Demography and Ecology.

Learn More About the CDWG

A group photo of the members of the Computational Demography Working Group

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/