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Agent-Based Knowledge Analysis Framework in Disaster Management
Authors:Dedi?Iskandar?Inan  author-information"  >  author-information__contact u-icon-before"  >  mailto:dedi.i.inan@student.uts.edu.au"   title="  dedi.i.inan@student.uts.edu.au"   itemprop="  email"   data-track="  click"   data-track-action="  Email author"   data-track-label="  "  >Email author,Ghassan?Beydoun,Simon?Opper
Affiliation:1.Departement Teknik Informatika,Universitas Negeri Papua,Manokwari,Indonesia;2.School of System, Management and Leadership,University of Technology Sydney,Ultimo,Australia;3.State Emergency Service New South Wales,Wollongong,Australia
Abstract:Disaster Management (DM) is a complex set of interrelated activities. The activities are often knowledge-intensive and time sensitive. Timely sharing of the required knowledge is critical for DM. For recurring disasters (e.g. floods), developed countries tend to have dedicated document repositories of Disaster Management Plans (DISPLANs) that can be accessed as needs arise. However, accessing the appropriate plan in a timely manner, and sharing activities between plans, often requires significant domain knowledge and intimate understanding of the plans in the first place. This paper introduces an Agent-Based (AB) knowledge analysis method to convert DISPLANs into a collection of knowledge units that can be stored into a unified repository. The repository of DM actions then enables the mixing and matching of knowledge between different plans. The repository is structured as a layered abstraction according to Meta Object Facility (MOF). We use the flood DISPLANs plans used by SES (State Emergency Service), an authoritative DM agency in New South Wales (NSW) State of Australia (hereinafter referred to as SES NSW) to illustrate and give a preliminary validation of the approach. It is illustrated by using displans along the flood-prone Murrumbidgee river in central NSW.
Keywords:
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