Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

5-2019

Abstract

We introduce Project Sidewalk, a new web-based tool that enables online crowdworkers to remotely label pedestrian-related accessibility problems by virtually walking through city streets in Google Street View. To train, engage, and sustain users, we apply basic game design principles such as interactive onboarding, mission-based tasks, and progress dashboards. In an 18-month deployment study, 797 online users contributed 205,385 labels and audited 2,941 miles of Washington DC streets. We compare behavioral and labeling quality differences between paid crowdworkers and volunteers, investigate the effects of label type, label severity, and majority vote on accuracy, and analyze common labeling errors. To complement these findings, we report on an interview study with three key stakeholder groups (N=14) soliciting reactions to our tool and methods. Our findings demonstrate the potential of virtually auditing urban accessibility and highlight tradeoffs between scalability and quality compared to traditional approaches.

Keywords

GIS, Mobility impairments, Accessibility, Crowdsourcing

Discipline

Databases and Information Systems | Geographic Information Sciences

Research Areas

Data Science and Engineering

Publication

CHI '19: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, Glasgow, Scotland, May 4-9

First Page

62:1

Last Page

14

ISBN

9781450359702

Identifier

10.1145/3290605.3300292

Publisher

ACM

City or Country

New York

Additional URL

https://doi.org/10.1145/3290605.3300292

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