Cities, organizations, and individuals currently lack detailed, accurate, and standardized data on the locations of footpaths, cycle paths, sidewalks, and crossings. Moreover, there is inconsistent information about the attributes of these pathways that affect walking, rolling, and non-motorized travel, as well as a limited understanding of how these paths are connected or disconnected.
The OpenSidewalks project aims to address this data deficiency by proposing a robust data schema and a comprehensive data tools ecosystem that support collection and maintenance of sidewalk data. These resources are designed to give planners, policy makers, and community advocates the data they need to improve pedestrian infrastructure, particularly in historically underserved areas.
OpenSidewalks envisions a future where an easy-to-understand, human-and-machine-readable schema empowers data producers to gather comprehensive information about the built environment through community engagement, crowd sourcing, and machine learning.
Project History
OpenSidewalks is led by the Taskar Center for Accessible Technology (TCAT) housed by the Paul G. Allen School for Computer Science and Engineering at the University of Washington. Current funding is provided by the USDOT/JPO ITS4US program under the University of Washington’s Transportation Data Equity Initiative (TDEI) deployment project.
The University of Washington’s eScience Institute provided an opportunity for the OpenSidewalks project to develop as a part of their Data Science for Social Good program that took place in the summer of 2016.
TCAT OpenSidewalks- WA State's OS-CONNECT dataset 