Tag: DSSG
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Microsoft $1M gift for new UW, UBC urban data partnership
By Robin Brooks The University of Washington and the University of British Columbia are partnering on a new collaboration called the Cascadia Urban Analytics Cooperative (CUAC), which will connect researchers, students and public stakeholders working on urban issues across the region. A $1 million donation from Microsoft will allow the two universities to work together using data…
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Data Science for Social Good collaboration nets WSDOT funding
By Robin Brooks A collaboration between two eScience Institute Data Science for Social Good (DSSG) project leads has resulted in a financial award which allows them to continue their work. Mark Hallenbeck, director of the Washington State Transportation Center, and Anat Caspi, director of the Taskar Center for Accessible Technology, both eScience fellows, answered questions submitted…
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DSSG projects highlighted in the media
By Robin Brooks The eScience Institute’s Data Science for Social Good fellows presented their final projects on August, 18th to a packed auditorium. The sixteen fellows have been working for the last ten weeks on four projects designed to tackle urban issues that might be solved with data analysis. The final presentations received media coverage (see…
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Meet the 2016 Data Science for Social Good fellows
By Robin Brooks Their schools, goals, specialties, countries and backgrounds vary. So what compels 16 college students to work full-time for a summer analyzing data? The eScience Institute‘s Data Science for Social Good program allows fellows the opportunity to develop new skills, learn from one another, and receive guidance from top-notch scientists on their project…
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Data Science for Social Good Program kicks off
By Robin Brooks The eScience Institute’s Data Science for Social Good (DSSG) program is in full swing this summer, with fellows from eight different universities participating in four data-intensive research projects. This year’s teams are focused on urban science, with each group aiming to extract and comprehend relevant, usable information out of data from metropolitan…