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Supporting Observers in the Field to Perform Model Based Data Collection
Linköping University, Department of Computer and Information Science. Linköping University, The Institute of Technology.
(English)Manuscript (Other academic)
Abstract [en]

Computerized support systems enhancing taskforce performance are being increasingly used in different organizations in the military, emergency response and crisis management fields. Computerized command and control (C2) systems and systems supporting concept development and experimentation (CD&E), training and capability development mostly handle data logged by technical systems, devices and sensors. Organizational demands for improved mission capabilities and reduced budgets impose new requirements on system performance and data content. More information needs to be provided by humans in the field, reporting observations from the evolving course of events in order to enhance possibilities for operational analyses and continuous development of organizational abilities. In this paper, we introduce model-based data collection (MBDC) and describe a method that can improve human datacollection abilities and data quality when using human observers as data collecting sensors in distributed tactical operations. Furthermore, we introduce a tool that can support observers in the field. The network-based observer tool (NBOT) can support human observers in determining what to report, and how and when to report the observation. It is possible to configure NBOT to meet different requirements, for example from a consideration of information needs, the field environment and available budget. We present results and findings from three different use cases.

National Category
Computer Science
URN: urn:nbn:se:liu:diva-15619OAI: diva2:126774
Available from: 2008-11-21 Created: 2008-11-21 Last updated: 2010-01-14
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.
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1386
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
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)
2008-12-18, Alan Turing, hus E, Campus Valla, Linköpings universitet, Linköping, 13:15 (Swedish)
Available from: 2008-11-21 Created: 2008-11-21 Last updated: 2009-05-15Bibliographically approved

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