Assessing uncertainty in VGI for emergency response

Abstract

This research project examines the geographic data produced by volunteers via the Ushahidi web platform in response to the earthquake that struck Haiti in January 2010. Volunteers translated messages (text, e-mail, and voice) submitted by victims of the earthquake, categorized each message into a primary ‘emergency need’ category and subcategory, and georeferenced each message on a dynamic web-based map. Initial inspection of the categorized data indicated discrepancies between the emergency need submitted by victims and the subsequent categorization of the emergency need. Analysis of the main categorical data illustrated that 50% of the messages were mis-categorized by the volunteers, failing to convey the main idea of the victim’s message. At the subcategory level, approximately 73% of the messages failed to convey the main idea of the messages. These numbers are higher than the estimate of 36% error in categorization produced in an independent review of the Haiti Ushahidi database. While the volunteer response to the Haitian earthquake represents a paradigm shift in emergency response and victim empowerment that has been repeated in numerous natural and man-made disasters around the world, this study suggests the need for more research on the quality of the categorization (i.e., attribute data) of volunteered emergency data.

Keywords:

• VGI
• uncertainty
• emergency response
• attribute quality
• GIS

Notes

1. Patrick Meier at Harvard began the Ushahidi mapping for Haiti. As the volume of tweets increased, he enlisted friends to help process the tweets. The volume of information continued to increase from multiple sources included tweets, social media, and traditional media, therefore 100 graduate and graduate students were enlisted from The Fletcher School at Tufts University (where Meier received his Ph.D.) to help monitor and map information. Mapping was difficult because of the paucity of geospatial data available in digital format, so OpenStreetMap volunteers used World Band supplied satellite imagery to trace roads. The short message system for Haitian Diaspora was created, resulting in thousands of messages – most were in Haitian Creole and needed to be translated. Additional volunteers from Haitian Diaspora in Boston translated the messages to English and helped to locate the messages on the map. So many messages were received that the graduate and undergraduate student volunteers triaged messages to focus on most serious life and death messages (Meier 2012).