October 11, 2003
knowledge domain visualization...
the knowledge landscape
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explore in 3D
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©2003 judith meskill
Visualizing a Knowledge Domain's Intellectual Structure
Knowledge Management and Knowledge Work are enhanced by effective information modeling and visualization tools. Knowledge domain visualization (KDV) assists in recognizing patterns of citation, not only in scientific journals but also in how organizations, industries, and the world at large refer to each other and give attribution or citation. Being a "visual" type, I find this area of study into visualizing a knowledge domain's intellectual structure in a three-dimensional spatial model compelling.
...To make knowledge visualizations clear and easy to interpret, the authors have developed a method that extends and transforms traditional author co-citation analysis (ACA) by extracting structural patterns from the scientific literature and representing them in a 3D knowledge landscape. Integrating citation and co-citation patterns provides a rich, ecological representation of a knowledge domain. Users can apply visualizations to discover patterns and make valuable connections among data. The authors' approach extends conventional ACA by integrating structured modeling and information visualization techniques to provide a 3D knowledge landscape based on citation patterns. Their four-step procedure introduces Pathfinder network scaling to replace multidimensional scaling. It also integrates Pathfinder and factor analysis to visualize specialties in the underlying domain knowledge and visualizes the citation frequency of scientists to track changes in their influence over time. This knowledge visualization approach identifies intellectual groupings based on extending the traditional ACA, augmenting the existing document- and concept-centered approaches to knowledge visualization. The 3D knowledge landscape has practical implications in knowledge visualization, digital libraries, domain analysis, and subject domains, providing powerful tools for tracking intuitively scientific knowledge...
For access to downloadable PDF papers in this area:
Dr. Chaomei Chen - is an Associate Professor in the College of Information Science and Technology at Drexel University. His research interests include information visualization, digital libraries, visualization of knowledge structures, and social dynamics in multi-user virtual environments. He is the author of Information Visualisation and Virtual Environments (Springer, 1999) and the Editor-in-Chief of a peer-reviewed international journal Information Visualization.
Katy Borner - is an Assistant Professor in Information Science at Indiana University. Trained as an engineer, her major interest has always been a concern with how existing technology can be applied to enhance and extend human capabilities. In particular, she focuses on information visualization and the usage of 3-D technology to build collaborative, intuitive and efficient human-computer interfaces to electronically available data such as text and image digital libraries.
For more information on Knowledge Domain Visualization, Google It!
K-CollectorOctober 11, 2003 11:45 AM | google it! | threadorati