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Data science for urban equity: Making gentrification an accessible topic for data scientists, policymakers, and the community


Created on 6th October 2017

Bernease Herman; Gundula Proksch; Rachel Berney; Hillary Dawkins; Jacob Kovacs; Yahui Ma; Jacob Rich; Amanda Tan;


The University of Washington eScience Institute runs an annual Data Science for Social Good (DSSG) program that selects four projects each year to train students from a wide range of disciplines while helping community members execute social good projects, often with an urban focus. We present observations and deliberations of one such project, the DSSG 2017 'Equitable Futures' project, which investigates the ongoing gentrification process and the increasingly inequitable access to opportunities in Seattle. Similar processes can be observed in many major cities. The project connects issues usually analyzed in the disciplines of the built environment, geography, sociology, economics, social work and city governments with data science methodologies and visualizations. Comments: Presented at the Data For Good Exchange 2017 Subjects: Computers and Society (cs.CY) Cite as: arXiv:1710.02447 [cs.CY]   (or arXiv:1710.02447v1 [cs.CY] for this version)

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# Status Date
1 Completed 12 Nov 2017 View review



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