TY - GEN
T1 - A Knowledge Management and Need-Capacity Matching Approach for Community-Based Disaster Management and Recovery
AU - Palomares, Iván
AU - Galway, Leo
AU - Haran, Martin
AU - Neef, Martijn
AU - Woods, Conor
AU - Wang, Hui
N1 - The 10th International Conference on Intelligent Systems and Knowledge Engineering ; Conference date: 01-01-2015
PY - 2016/1/14
Y1 - 2016/1/14
N2 - Post-crisis response and recovery necessitates the identification and prioritization of the needs and capacities of the affected community in order to provide efficient and well- coordinated humanitarian assistance. The Community Based Comprehensive Recovery platform aims to facilitate enhanced communication flows between professional communities, af- fected communities, and volunteer responders to enhance situational awareness, inform and guide response planning, and ensure more effective coordination of activities by volunteer responders. Underpinning the platform, an information frame- work has been designed to support acquisition and analysis of the needs and capacities that arise across affected communities. In addition, a multi-criteria decision making algorithm has been designed and developed in order to enhance sense making and situational awareness within the platform. Subsequently, this paper introduces the core concepts that provide a basis for the information model, along with the associated ontology. Furthermore, the paper presents details of the decision making algorithm in conjunction with results from its application to a representative set of sample data.
AB - Post-crisis response and recovery necessitates the identification and prioritization of the needs and capacities of the affected community in order to provide efficient and well- coordinated humanitarian assistance. The Community Based Comprehensive Recovery platform aims to facilitate enhanced communication flows between professional communities, af- fected communities, and volunteer responders to enhance situational awareness, inform and guide response planning, and ensure more effective coordination of activities by volunteer responders. Underpinning the platform, an information frame- work has been designed to support acquisition and analysis of the needs and capacities that arise across affected communities. In addition, a multi-criteria decision making algorithm has been designed and developed in order to enhance sense making and situational awareness within the platform. Subsequently, this paper introduces the core concepts that provide a basis for the information model, along with the associated ontology. Furthermore, the paper presents details of the decision making algorithm in conjunction with results from its application to a representative set of sample data.
KW - Disaster Recovery
KW - Information and Ontology Modeling
KW - Multi-Criteria Decision Making
U2 - 10.1109/ISKE.2015.37
DO - 10.1109/ISKE.2015.37
M3 - Conference contribution
T3 - International Conference on Intelligent Systems and Knowledge Engineering (ISKE)
SP - 389
EP - 396
BT - 2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE): Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
CY - United States
ER -