Ulster University Logo

A Knowledge Management and Need-Capacity Matching Approach for Community-Based Disaster Management and Recovery

Palomares, Iván, Galway, Leo, Haran, Martin, Woods, Conor and Wang, Hui (2015) A Knowledge Management and Need-Capacity Matching Approach for Community-Based Disaster Management and Recovery. In: The 10th International Conference on Intelligent Systems and Knowledge Engineering, Taipei, Taiwan. IEEE. 8 pp. [Conference contribution]

Full text not available from this repository.

Abstract

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.

Item Type:Conference contribution (Paper)
Keywords:Disaster Recovery; Information and Ontology Modeling; Multi-Criteria Decision Making
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Faculty of Art, Design and the Built Environment
Faculty of Art, Design and the Built Environment > School of the Built Environment
Research Institutes and Groups:Built Environment Research Institute > Centre for Research on Property and Planning (RPP)
Built Environment Research Institute
Computer Science Research Institute > Smart Environments
Computer Science Research Institute
Computer Science Research Institute > Artificial Intelligence and Applications
ID Code:32886
Deposited By: Dr Leo Galway
Deposited On:21 Dec 2015 10:05
Last Modified:21 Dec 2015 10:05

Repository Staff Only: item control page