DFG Initiative of Excellence, HeiKa Programme


Crowd FDA: Crowdsourcing for Forensic Disaster Analysis

The aftermath of disasters – such as the recent Nepal earthquake – have shown that the general public can contribute to the response of a disaster event and moreover is able to organize and engage itself across national borders. Digital volunteerism is offering unique capabilities to bridge information gaps, particularly in crisis situations where infrastructure is broken or crisis response mechanisms are overloaded. Crowdsourcing offers the capacity to quickly process huge amounts of data and might represent the only source of information in certain situations. Consequently, crowdsourcing and Volunteered Geographic Information (VGI) are useful to complete official information for decision makers and emergency responders in crisis situations. This, however, raises the question of how such often poorly structured information can be incorporated into response plans in a disaster event. This faces a major problem: What is lacking in the field of crisis informatics is a conceptual scientific framework to integrate and operationalize crisis crowdsourcing into the official emergency management environment. (Liu, 2014). To solve this problem the proposed project seeks to develop a scientific framework for using crowdsourcing to generate insight about the potential emerging issues, causes and consequences of losses in disasters. This will be accomplished by bridging the competencies and complimentary expertise in near real-time Forensic Disaster Analysis (FDA) at the Center for Disaster Management and Risk Reduction Technology (CEDIM, KIT) with expertise available in Volunteered Geographic Information (VGI) at the GIScience Research Group of Heidelberg University. The main result is the development of a Crowdsourcing for Forensic Disaster Analysis (Crowd FDA) scientific framework and novel methods. These will be operationalized in disaster event(s) during the project with respect to sheltering of displaced populations as a pilot application area.

Figure: CrowdFDA framework


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