Building a geospatial data model for humanitarian response.

Abstract

An effectual emergency response effort is contingent upon the quality and timeliness of information provided to both the decision making and coordinating functions; conditions that are hard to guarantee in the urgent climate of the response effort. The purpose of this paper is to present a validated Humanitarian Data Model (HDM) that can assist in the rapid assessment of disaster needs and subsequent decision making. Substandard, inconsistent information can lead to poorly informed decisions, and subsequently, inappropriate response activities. Here we present a novel, organized, and fluid information management workflow to be applied during the rapid assessment phase of an emergency response. A comprehensive, peer-reviewed geospatial data model not only directs the design of data collection tools but also allows for more systematic data collection and management, leading to improved analysis and response outcomes. This research involved the development of a comprehensive geospatial data model to guide the collection, management and analysis of geographically referenced assessment information, for implementation at the rapid response phase of a disaster using a mobile data collection app based on key outcome parameters. A systematic review of literature and best practices was used to identify and prioritize the minimum essential data variables. The data model was critiqued for variable content, structure, and usability by a group of subject matter experts in the fields of humanitarian information management and geographical information systems. Consensus found that the adoption of a standardized system of data collection, management, and processing, such as the data model presented here, could facilitate the collection and sharing of information between agencies with similar goals, facilitate the better coordination of efforts by unleashing the power of geographic information for humanitarian decision support.