While street networks and land use are frequently mapped, including by our public agencies, our experiences as pedestrians are rarely supported through data. As a result, while automatic trip finding, certain kinds of transit analysis, and traffic questions are well-supported by data, the pedestrian experience is not. As a result, we can’t ask seemingly simple questions like, “can I get to this public service from this bus stop?”, a question that intersects with disability, age, and economic inequality (among other topics). The OpenSidewalks project intends to bridge this data gap by openly defining, collecting, and using large-scale pedestrian networks. Building on OpenStreetMap, OpenSidewalks helps define a standard way by which to use existing OpenStreetMap “tags” to build a coherent pedestrian network as open data. We then take this standard and build around it crowdsourced, community mapping infrastructure and volunteer events, as well as build partnerships with agencies and other organizations interested in creating and maintaining these data. Next, we focus on (re)publishing these data in a format that is more accessible to data practitioners, particularly those who work with network analysis. Finally, we create projects that consume these data, such as the AccessMap project that creates pedestrian trip plans according to individuals’ needs and preferences. This talk will cover these topics, including our approach to de-stereotyping data representations of disability as well as recent pilots in remotely mapping cities at scale.
This seminar is co-organized with UW CREATE.
My research focuses on the intersection between pedestrian mobility, data science, and computer science. I work on defining, collecting, producing user-facing tools for, and analyzing pedestrian network data - data that is otherwise rarely collected but exposes serious inequities and accessibility concerns in our public spaces. My PhD work focused on two projects, OpenSidewalks and AccessMap. OpenSidewalks is a project for openly defining, creating, and analyzing pedestrian network data, particularly in OpenStreetMap. AccessMap is a user-facing information retrieval tool, an interactive map that adapts to an individual’s preferences when navigating the built environment: if a person requires curb ramps, it will avoid raised curbs and if a person cannot go up steep hills, it will avoid them, while still providing a realistic path from a start point to an end point. My current research extends on these projects to include a larger number of cities, promote integration between municipalities and OpenSidewalks datasets, and understand pedestrian accessibility on city and regional scales.