As a data science hub, eScience has a network of partnerships, within and beyond UW.
Our partners are organizations that use data science in a number of different ways. We are able to connect etc. etc. The eScience Institute empowers researchers and students in all fields to answer fundamental questions through the use of large, complex, and noise
yond to make sense of their large datasets. Data science tools like machine learning, data visualizations, and cloud computing can be applied to a variety of fields, and eScience is the hub where they all come together.
University of Washington
Support from the University of Washington (UW) enabled the creation of the eScience Institute in 2008, and demonstrated the UW’s commitment to helping faculty and researchers meet the challenge of computational knowledge extraction in all fields of science and engineering. The UW hosts the eScience Institute as a virtual organization across campus and provides the data center facility housing the computational platforms designed and deployed by the Institute. The support provided by the UW creates opportunities to reduce cost, minimize duplication of effort, and allows faculty and researchers to focus on their science.
University of Washington Libraries
The University of Washington Libraries advances intellectual discovery and enriches the quality of life by connecting people with knowledge. It is a user-centered academic library with rich collections, collaborations and partnerships, ranked in the top ten of U.S. public research universities according to the Association of Research Libraries.
Institute for Foundations of Data Science
At the Institute for Foundations of Data Science (IFDS), Data science is making an enormous impact on science and society, but its success is uncovering pressing new challenges that stand in the way of further progress. Outcomes and decisions arising from many machine learning processes are not robust to errors and corruption in the data; data science algorithms are yielding biased and unfair outcomes, as concerns about data privacy continue to mount; and machine learning systems suited to dynamic, interactive environments are less well developed than corresponding tools for static problems. Only by an appeal to the foundations of data science can we understand and address challenges such as these.
UW Institute for Neuroengineering
With support from the Washington Research Foundation, the University of Washington Institute for Neuroengineering collectively draws on the unique strengths of computing, engineering, and neuroscience to support a rich array of research and educational programs. We will develop the next generation of devices and algorithms that assist individuals with neural and mobility disorders (e.g. traumatic brain and spinal cord injury, multiple sclerosis, Parkinson’s disease, and epilepsy). Further, inspired by neural systems, we will develop interactive and autonomous devices that can be used for assistance within the home and for exploration in the remote regions of the planet and in space.
UW Computational Neuroscience Center
The University of Washington’s Computational Neuroscience Center is a focal point for research in mathematical and computational neuroscience spanning the full spectrum of scales, mechanisms, and functions of the brain — from ion channel stochasticity in auditory processing to insect flight control to human/computer interfaces. The Center, which also houses the Swartz Center for Theoretical Neuroscience, is the campus home for undergraduate, graduate and postdoctoral training and research programs linking theoretical and experimental neuroscience to advance understanding of the principles of neural computation.
The Data Intensive Research in Astrophysics and Cosmology (DIRAC) Institute is a world leading, interdisciplinary research center that addresses fundamental questions about the origins and evolution of the universe. Our research brings together scientists across many disciplines on a mission to understand the nature of dark matter and dark energy, the emergence of structure within the universe, the formation of galaxies, the birth and evolution of black holes, the transformations of stars, and the origins of the planets.
The Allen Institute works to unlock the complexities of bioscience and advance their knowledge to improve human health. Using an open science, multi-scale, team-oriented approach, the Allen Institute focuses on accelerating foundational research, developing standards and models, and cultivating new ideas to make a broad, transformational impact on science. They tackle large-scale, ambitious projects that yield rich, robust data. The Allen Institute integrates this data with sophisticated technology so that it can be readily shared with the global scientific community for exploration and analysis.
Cascadia Data Alliance
The Cascadia Data Alliance (CDA) is a first step toward achieving a regional data sharing ecosystem. CDA will enable sharing of metadata (descriptive information about underlying data) to facilitate data discovery so researchers can find interesting and unique datasets more quickly. CDA will collect and curate governance documentation and will establish additional governance support to accelerate sharing of the underlying data between researchers at participating organizations.
Urban@UW extends the understanding of cities — from people, buildings, infrastructure, and energy to economics, policy, culture, art, and nature — beyond individual topics to dynamically interdependent systems, so that we can holistically design and steward vibrant and welcoming cities in which future generations will thrive. Together, we will catalyze the growth of Seattle as a model city — a boundary-pushing laboratory and knowledge economy hub that leverages innovation to create a place of opportunity and health for all — and build knowledge that can be used in metropolitan regions around the globe. Urban@UW leverages deep understanding, leading-edge analysis, and an ethos of partnership to create the pathway for Seattle as the city of the future.
The Urbanalytics Studio will bridge expertise from the eScience Institute, the Center for Studies in Demography and Ecology (CSDE), and faculty from across the Urban@UW network to establish a permanent capacity for high-impact data-driven analytics and research projects on behalf of government and community stakeholders, addressing the complex challenges and opportunities of the urban landscape.
Center for Studies in Demography & Ecology
The Center for Studies in Demography and Ecology (CSDE) supports population research and training at the University of Washington by advancing knowledge on migration, health, family change, and other demographic trends. CSDE is a community of faculty and students associated to advance population science through research and training. As a federally funded research center with over 70 years of experience, the CSDE community of scholars develops new demographic measures and methods, advances knowledge about population dynamics, generates new data and evidence to support population science, and trains the next generation of demographers.
Qualitative Multi-Method Research Program
The Qualitative Multi-Method Program (QUAL) is a UW-wide initiative launched in response to pressing demand for qualitative research design and methods in universities, the private sector, and government. QUAL’s goal is to promote teaching and research related to qualitative methodology, and to foster a professional community of qualitative multi-method researchers.
West Big Data Innovation Hub
The West Big Data Innovation Hub builds partnerships across academia, industry, nonprofits, and government to address societal challenges with Big Data Innovation. The goals are to accelerate innovation on national priorities, foster cross-cutting teams and strengthen the west data science community.
The MetroLab Network is a group of more than 35 city-university partnerships focused on bringing data, analytics, and innovation to city government. Its members include 44 cities, 5 counties, and 59 universities. The Network’s mission is to pair university researchers with city policymakers to undertake research, development, and deployment projects that improve our infrastructure, public services, and environmental sustainability. The Network was launched as part of the White House’s Smart Cities Initiative in September 2015.
Moore-Sloan Data Science Environments
Moore – Sloan Data Science Environments seek to enhance data-driven discovery by supporting cross-disciplinary academic data scientists at research institutions. Our work is organized around six challenges – careers, education and training, tools and software, reproducibility and open science, physical and intellectual space, ethnography, and evaluation – which are themes used to effectively focus our efforts to advance the future of academic data science. We have created three Data Science Environments – the University of Washington’s eScience Institute, Berkeley Institute for Data Science, and NYU Center for Data Science – to work toward our goals.
Berkeley Institute for Data Science
Founded in 2013, the Berkeley Institute for Data Science (BIDS) is a central hub of research and education within the University of California, Berkeley designed to facilitate and nurture data-intensive science. BIDS initiatives are designed to bring together a broad constituency of the data science community, including domain experts from the life, social, and physical sciences and methodological experts from computer science, statistics, and applied mathematics. These efforts are anchored by a core group of data science fellows and senior fellows who are representative of the world-class researchers from across campus and are leading the data science revolution within their disciplines.
NYU Center for Data Science
The NYU Center for Data Science (CDS) is a university-wide initiative that was established to foster research and education in data science. It is interdisciplinary and cross-school, with participation by faculty from many New York University units. The CDS brings together computer scientists and domain scientists with complex data science problems to capitalize on common interests, develop and apply computational methods to solve real problems, and build shared resources that can benefit research groups at NYU and worldwide, and consequently help advance data-driven scientific discovery.
Bill & Melinda Gates Foundation
Guided by the belief that every life has equal value, the Bill & Melinda Gates Foundation works to help all people lead healthy, productive lives. In developing countries, it focuses on improving people’s health and giving them the chance to lift themselves out of hunger and extreme poverty. In the United States, it seeks to ensure that all people — especially those with the fewest resources — have access to the opportunities they need to succeed in school and life.
Intl. Neuroinformatics Coordinating Facility
The mission of International Neuroinformatics Coordinating Facility (INCF) is to develop, evaluate, and endorse standards and best practices that embrace the principles of Open, FAIR, and Citable neuroscience. INCF also provides training on how standards and best practices facilitate reproducibility and enables the publishing of the entirety of research output, including data and code.
Institute of Translational Health Sciences
The Institute of Translational Health Sciences provides access to information, services, funding and training for research teams working on translational science questions. Within ITHS, the Biomedical Informatics Core is a resource for service, education, and innovation in the management of clinical and translational biomedical data.
Clean Energy Institute
The Clean Energy Institute (CEI) supports the advancement of next-generation solar energy and battery materials and devices, as well as their integration with systems and the grid. The CEI creates the ideas and educates the people needed to generate those innovations, while facilitating the pathways to bring them to market.
Institute for Protein Design
The exquisite functions of naturally occurring proteins solve the challenges faced during evolution. However, we face challenges today that were not faced during natural evolution. The goal of the Institute for Protein Design is to develop and apply methods for designing a whole new world of synthetic proteins to address these challenges..
Cascadia Urban Analytics Cooperative
The specific focus of the Cascadia Urban Analytics Cooperative (CUAC) is data science for social good in an urban context: high-impact data science and analytics projects that aim to understand and extract valuable actionable information out of data from urban environments in the Cascadia region at a neighborhood level. To lead a focused response, the University of Washington (through a partnership between the eScience Institute, Urbanalytics and Urban@UW) and the University of British Columbia (through a partnership between UBC’s Data Science Institute and UBC’s Sustainability Initiative) have formed CUAC, an applied, interdisciplinary, regional center that brings together academic researchers, students, and public stakeholder groups to address topics affecting the region