A geovisual analytics exploration of the OpenStreetMap crowd

ABSTRACT

It is sometimes easy to forget that massive crowdsourced data products such as Wikipedia and OpenStreetMap (OSM) are the sum of individual human efforts stemming from a variety of personal and institutional interests. We present a geovisual analytics tool called Crowd Lens for OpenStreetMap designed to help professional users of OSM make sense of the characteristics of the “crowd” that constructed OSM in specific places. The tool uses small multiple maps to visualize each contributor’s piece of the crowdsourced whole, and links OSM features with the free-form commit messages supplied by their contributors. Crowd Lens allows sorting and filtering contributors by characteristics such as number of contributions, most common language used, and OSM attribute tags applied. We describe the development and evaluation of Crowd Lens, showing how a multiple-stage user-centered design process (including testing by geospatial technology professionals) helped shape the tool’s interface and capabilities. We also present a case study using Crowd Lens to examine cities in six continents. Our findings should assist institutions deliberating OSM’s fitness for use for different applications. Crowd Lens is also potentially informative for researchers studying Internet participation divides and ways that crowdsourced products can be better comprehended with visual analytics methods.

KEYWORDS:

• OpenStreetMap
• volunteered geographic information
• crowdsourcing
• geovisual analytics
• scenario-based design

Acknowledgments

We are grateful to Greg Milbourne for assistance with data processing and early application prototyping. We also thank the editor and anonymous reviewers for their suggestions on the text and graphics.

Disclosure statement

No potential conflict of interest was reported by the authors.