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Data Collection in Rescue Operations
Linköping University, Department of Computer and Information Science. Linköping University, The Institute of Technology.
2002 (English)In: The International Emergency Management Society 9th Annual Conference Proceedings, 2002, 136-147 p.Conference paper, Published paper (Other academic)
Abstract [en]

Rescue operations are complex distributed activities. First response, incident command and rear support have to be coordinated under time pressure and safety critical conditions. Analysing an operation and learning from the experience is problematic because spatially separated units, heterogeneous systems and fragmentary information make it difficult for participants, managers and researchers to grasp the ramifications of a complex scenario. In training, multimedia representations of rescue operations support after-action reviews, post-mission analyses and distance learning by providing coherent and persistent representations of exercises. In this paper we investigate how methods and tools developed in a training context can be adapted to support reconstruction and exploration of real rescue operations as a basis for experience-based learning and operational development. Especially, we study the requirements and limitations on data collection in real rescue operations in relation to emergency-response training. We elaborate on the consequences of the differences in data collection abilities for documenting an involved scenario, analysing the facts of the event and communicating the results and findings.

Place, publisher, year, edition, pages
2002. 136-147 p.
Keyword [en]
Rescue operations, data collection, debriefing, AAR, learning
National Category
Computer Science
Identifiers
URN: urn:nbn:se:liu:diva-15618OAI: oai:DiVA.org:liu-15618DiVA: diva2:126773
Available from: 2008-11-21 Created: 2008-11-21 Last updated: 2009-04-14
In thesis
1. Using Observers for Model Based Data Collection in Distributed Tactical Operations
Open this publication in new window or tab >>Using Observers for Model Based Data Collection in Distributed Tactical Operations
2008 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Modern information technology increases the use of computers in training systems as well as in command-and-control systems in military services and public-safety organizations. This computerization combined with new threats present a challenging complexity. Situational awareness in evolving distributed operations and follow-up in training systems depends on humans in the field reporting observations of events. The use of this observer-reported information can be largely improved by implementation of models supporting both reporting and computer representation of objects and phenomena in operations.

This thesis characterises and describes observer model-based data collection in distributed tactical operations, where multiple, dispersed units work to achieve common goals. Reconstruction and exploration of multimedia representations of operations is becoming an established means for supporting taskforce training. We explore how modelling of operational processes and entities can support observer data collection and increase information content in mission histories. We use realistic exercises for testing developed models, methods and tools for observer data collection and transfer results to live operations.

The main contribution of this thesis is the systematic description of the model-based approach to using observers for data collection. Methodological aspects in using humans to collect data to be used in information systems, and also modelling aspects for phenomena occurring in emergency response and communication areas contribute to the body of research. We describe a general methodology for using human observers to collect adequate data for use in information systems. In addition, we describe methods and tools to collect data on the chain of medical attendance in emergency response exercises, and on command-and-control processes in several domains.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2008. 75 p.
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1386
Keyword
Observers, model-based data collection, distributed tactical operations, taskforce training, communication analysis, reconstruction & exploration, extended link analysis, timed checkpoints, network based observer tool
National Category
Computer Science
Identifiers
urn:nbn:se:liu:diva-15620 (URN)LiU-Tek-Lic-2008:44 (Local ID)978-91-7393-751-1 (ISBN)LiU-Tek-Lic-2008:44 (Archive number)LiU-Tek-Lic-2008:44 (OAI)
Presentation
2008-12-18, Alan Turing, hus E, Campus Valla, Linköpings universitet, Linköping, 13:15 (Swedish)
Opponent
Supervisors
Available from: 2008-11-21 Created: 2008-11-21 Last updated: 2009-05-15Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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Language
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Output format
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  • asciidoc
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