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

Iván Palomares, Leo Galway, Martin Haran, Conor Woods, Hui Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.
Original languageEnglish
Title of host publicationUnknown Host Publication
PublisherIEEE
Number of pages8
Publication statusPublished - 2015
EventThe 10th International Conference on Intelligent Systems and Knowledge Engineering - Taipei, Taiwan
Duration: 1 Jan 2015 → …

Conference

ConferenceThe 10th International Conference on Intelligent Systems and Knowledge Engineering
Period1/01/15 → …

Keywords

  • Disaster Recovery
  • Information and Ontology Modeling
  • Multi-Criteria Decision Making

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