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Best of Both Worlds : Hybrid Knowledge Visualization in Police Crime Fighting and Military Operations
Type
conference paper
Date Issued
2013-09-04
Author(s)
Pfister, Roland
Editor(s)
Lindstaedt, Stefanie
Granitzer, Michael
Abstract
Making effective and timely use of all available, relevant knowledge is a major requirement for today's police officers who strive to fight organized crime or resolve complex criminal acts under time pressure. As they share this knowledge integration challenge with many management contexts, we have examined the knowledge visualization practices of a leading regional police force (and of a military unit) in order to derive insights for corporate knowledge management. To do so, we have conducted on-site observations, focus groups, and interviews, as well as site-, document-, tool- and software- analyses within the police headquarters. As one main result of our empirical investigation, we find that the police force's practice of hybrid (i.e., digital and physical) knowledge visualization offers a useful strategy for corporate knowledge management as well. We also show how organizations can apply this dual approach to making knowledge visible i.e., using sophisticated visualization software in combination with hands-on physical and permanently visible knowledge boards. We discuss how these two modalities can be combined to improve knowledge management and how this hybrid practice can be understood theoretically through the lens of boundary object theory. With this regard, we also extend boundary object theory by identifying nine dynamic qualities of collaborative visualizations.
Language
English
HSG Classification
contribution to practical use / society
Refereed
Yes
Book title
i-KNOW 2013 : proceedings of the 13th International Conference on Knowledge Management and Knowledge Technologies
Publisher
ACM
Publisher place
New York
Event Title
13th International Conference on Knowledge Management and Knowledge Technologies (I-KNOW)
Event Location
Graz
Event Date
04.-06.09.2013
Subject(s)
Division(s)
Eprints ID
232301