Please join us Tuesday for the first Change seminar of the new academic year! We will be in *Johnson Hall* *111 *this quarter.
*Who:* Jon Froehlich, UW CSE *What:* Project Sidewalk: Mapping the Accessibility of the World through Google Street View *When: Tuesday, Oct 9th, 12-1pm* *Where: **Johnson Hall 111* *Project Sidewalk: Mapping the Accessibility of the World through Google Street View* Digital maps such as Google Maps, Waze, and Yelp have transformed the way people travel and access information about the physical world. While these systems contain terabytes of data about road networks and points of interest (POIs), their information about physical accessibility is commensurately poor. GIS websites like Axsmap.com, Wheelmap.org, and AccessTogether.org aim to address this problem by collecting location-based accessibility information provided by volunteers (i.e., crowdsourcing). While these efforts are important and commendable, their value propositions are intrinsically tied to the amount and quality of data they collect. In a recent review of accessibility-oriented GIS sites, Ding et al. found that most suffered from serious data sparseness issues. One key limiting factor is the reliance on local populations with physical experience of a place for data collection. While local users who report data are likely to be reliable, the dependence on in situ reporting dramatically limits scalability—both who can supply data and how much data they can easily supply. In contrast, we are exploring a different approach embodied in a new interactive tool called Project Sidewalk (http://projectsidewalk.io), which enables online crowdworkers to contribute physical-world accessibility information by virtually walking through city streets in Google Street View (GSV)—similar to a first-person video game. Rather than pulling solely from local populations, our potential pool of users scales to anyone with an Internet connection and a web browser. In this talk, I will describe the design of Project Sidewalk and a recent 18-month deployment study in Washington DC. I will close with a discussion of our current and future work investigating correlates to urban accessibility, training machine learning algorithms to automatically assess accessibility, and interactive tools that create better transparency about accessible infrastructure. Our overarching goal is to transform how accessibility data is collected and visualized. *Bio:* http://www.cs.umd.edu/~jonf/ I received my Phd in Computer Science from the University of Washington in December 2011 where I was a Microsoft Research Graduate Fellow and the 2010 College of Engineering "Graduate Innovator of the Year." My PhD dissertation entitled "Sensing and Feedback of Everyday Activities to Promote Environmental Behaviors" won numerous awards including the 2012 University of Washington Distinguished Dissertation Award and an honorable mention for the national 2012 Council of Graduate Schools Distinguished Dissertation Award in Mathematics, Physical Sciences, and Engineering. At UW, I was co-advised by James Landay and Shwetak Patel. I also have an MS in Information and Computer Science from the University of California, Irvine where I was advised by Paul Dourish. During my graduate studies, I was fortunate to intern at a number of great research labs including Telefonica Research in Barcelona, Microsoft Research in Redmond, and Intel Research in Seattle. We will try to get a livestream up for this talk.
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