{"id":{"repo_id":"unm","oai_identifier":"oai:digitalrepository.unm.edu:geog_etds-1017"},"canonical_url":"https://search.dev.ndltd.org/etd/unm/oai:digitalrepository.unm.edu:geog_etds-1017","repository":{"repo_id":"unm","name":"University of New Mexico","base_url":"https://digitalrepository.unm.edu/do/oai/"},"display":{"title":"Assessing Uncertainty in Volunteered Geographic Information for Emergency Response","abstract":"This research project examines data produced by volunteers through the Ushahidi web platform in response to the earthquake that struck Haiti in January 2010. Volunteers translated messages submitted by victims in Haiti, categorized each message based on its content, and georeferenced each message on a dynamic web based map. When categorizing the data, volunteers were able to assign up to 8 main and 42 subcategories to each message. Initial inspection of the attribute data produced by the volunteers indicated a strong discrepancy between the contents of the messages submitted by the victims and the corresponding attributes assigned to those messages by the volunteers. By comparing the attributes of the data originally produced by the volunteers to data that I re-categorized, I was able to examine the degree of inconsistency among the attribute data produced by the volunteers. I found that only 26.59% of the messages submitted by the victims were consistently categorized compared to the data set that I re-categorized. However, when aggregating the subcategories up to their appropriate main category, I found 49.88% of messages were consistently categorized indicating that approximately half of the messages were conveying the main idea or ideas of the victims messages. These numbers are significantly lower than the estimate of 64% correct categorization produced by an independent review of the Ushahidi platform. Despite these low indicators of consistent categorization, 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.'","abstract_html":"This research project examines data produced by volunteers through the Ushahidi web platform in response to the earthquake that struck Haiti in January 2010. Volunteers translated messages submitted by victims in Haiti, categorized each message based on its content, and georeferenced each message on a dynamic web based map. When categorizing the data, volunteers were able to assign up to 8 main and 42 subcategories to each message. Initial inspection of the attribute data produced by the volunteers indicated a strong discrepancy between the contents of the messages submitted by the victims and the corresponding attributes assigned to those messages by the volunteers. By comparing the attributes of the data originally produced by the volunteers to data that I re-categorized, I was able to examine the degree of inconsistency among the attribute data produced by the volunteers. I found that only 26.59% of the messages submitted by the victims were consistently categorized compared to the data set that I re-categorized. However, when aggregating the subcategories up to their appropriate main category, I found 49.88% of messages were consistently categorized indicating that approximately half of the messages were conveying the main idea or ideas of the victims messages. These numbers are significantly lower than the estimate of 64% correct categorization produced by an independent review of the Ushahidi platform. Despite these low indicators of consistent categorization, 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.'","abstract_has_math":false,"creators":["Camponovo, Michael"],"institution":null,"degree_name":"Geography","degree_level":"Masters","degree_discipline":"Geography","degree_department":null,"school":null,"contributors":["Freundschuh, Scott","Benedict, Karl","Lippitt, Christopher"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2013,"date_issued":"2013-09-03T07:00:00Z","date_published":"2013-09-03T07:00:00Z","updated_at":"2026-07-24T05:27:31Z","subjects":["Geography","GIS","VGI","Ushahidi"],"languages":["English"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalrepository.unm.edu/geog_etds/18"],"render_values":[{"text":"https://digitalrepository.unm.edu/geog_etds/18","href":"https://digitalrepository.unm.edu/geog_etds/18","code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/1928/23260","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Freundschuh, Scott","Benedict, Karl","Lippitt, Christopher"]},{"key":"dc:creator","label":"Author","values":["Camponovo, Michael"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Geography"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Masters","Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Geography"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Geography","GIS","VGI","Ushahidi"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/1928/23260","https://digitalrepository.unm.edu/geog_etds/18"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This research project examines data produced by volunteers through the Ushahidi web platform in response to the earthquake that struck Haiti in January 2010. Volunteers translated messages submitted by victims in Haiti, categorized each message based on its content, and georeferenced each message on a dynamic web based map. When categorizing the data, volunteers were able to assign up to 8 main and 42 subcategories to each message. Initial inspection of the attribute data produced by the volunteers indicated a strong discrepancy between the contents of the messages submitted by the victims and the corresponding attributes assigned to those messages by the volunteers. By comparing the attributes of the data originally produced by the volunteers to data that I re-categorized, I was able to examine the degree of inconsistency among the attribute data produced by the volunteers. I found that only 26.59% of the messages submitted by the victims were consistently categorized compared to the data set that I re-categorized. However, when aggregating the subcategories up to their appropriate main category, I found 49.88% of messages were consistently categorized indicating that approximately half of the messages were conveying the main idea or ideas of the victims messages. These numbers are significantly lower than the estimate of 64% correct categorization produced by an independent review of the Ushahidi platform. Despite these low indicators of consistent categorization, 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.'"]},{"key":"dc:title","label":"Title","values":["Assessing Uncertainty in Volunteered Geographic Information for Emergency Response"]}]}],"canonical_facts":{"dc:contributor":["Freundschuh, Scott","Benedict, Karl","Lippitt, Christopher"],"dc:creator":["Camponovo, Michael"],"dc:description.abstract":["This research project examines data produced by volunteers through the Ushahidi web platform in response to the earthquake that struck Haiti in January 2010. Volunteers translated messages submitted by victims in Haiti, categorized each message based on its content, and georeferenced each message on a dynamic web based map. When categorizing the data, volunteers were able to assign up to 8 main and 42 subcategories to each message. Initial inspection of the attribute data produced by the volunteers indicated a strong discrepancy between the contents of the messages submitted by the victims and the corresponding attributes assigned to those messages by the volunteers. By comparing the attributes of the data originally produced by the volunteers to data that I re-categorized, I was able to examine the degree of inconsistency among the attribute data produced by the volunteers. I found that only 26.59% of the messages submitted by the victims were consistently categorized compared to the data set that I re-categorized. However, when aggregating the subcategories up to their appropriate main category, I found 49.88% of messages were consistently categorized indicating that approximately half of the messages were conveying the main idea or ideas of the victims messages. These numbers are significantly lower than the estimate of 64% correct categorization produced by an independent review of the Ushahidi platform. Despite these low indicators of consistent categorization, 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.'"],"dc:identifier":["http://hdl.handle.net/1928/23260","https://digitalrepository.unm.edu/geog_etds/18"],"dc:language":["English"],"dc:subject":["Geography","GIS","VGI","Ushahidi"],"dc:title":["Assessing Uncertainty in Volunteered Geographic Information for Emergency Response"],"thesis:degree_discipline":["Geography"],"thesis:degree_level":["Masters","Thesis"],"thesis:degree_name":["Geography"]},"updated_at":"2026-07-24T05:27:31Z"}