Envisioning information
Introduction to collaborative visualization
ACM SIGGRAPH Computer Graphics
Working Knowledge: How Organizations Manage What They Know
Working Knowledge: How Organizations Manage What They Know
Verification and Validation of Knowledge-Based Systems
IEEE Transactions on Knowledge and Data Engineering
IV '04 Proceedings of the Information Visualisation, Eighth International Conference
Ontology-based Active Requirements Engineering Framework
APSEC '05 Proceedings of the 12th Asia-Pacific Software Engineering Conference
Enabling community access to TeraGrid visualization resources: Research Articles
Concurrency and Computation: Practice & Experience - Science Gateways—Common Community Interfaces to Grid Resources
Creating a collaborative space to share data, visualization, and knowledge
ACM SIGGRAPH Computer Graphics
Legible Simplification of Textured Urban Models
IEEE Computer Graphics and Applications
Data, Information, and Knowledge in Visualization
IEEE Computer Graphics and Applications
Defining Insight for Visual Analytics
IEEE Computer Graphics and Applications
Finding business information by visualizing enterprise document activity
Proceedings of the International Conference on Advanced Visual Interfaces
Designing visual analytics systems for organizational environments
Proceedings of the 2011 Visual Information Communication - International Symposium
User-centered visual analysis using a hybrid reasoning architecture for intensive care units
Decision Support Systems
An interactive visual analytics system for bridge management
EuroVis'10 Proceedings of the 12th Eurographics / IEEE - VGTC conference on Visualization
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Knowledge-assisted visualization has been a fast growing field because it directly integrates and utilizes domain knowledge to produce effective data visualization. However, most existing knowledge-assisted visualization applications focus on integrating domain knowledge that is tailored only for specific analytical tasks. This reflects not only the different understandings of what ''knowledge'' is in visualization, but also the difficulties in generalizing and reapplying knowledge to new problems or domains. In this paper, we differentiate knowledge into two types, tacit and explicit, and suggest four conversion processes between them (internalization, externalization, collaboration, and combination) that could be included in knowledge-assisted visualizations. We demonstrate the applications of these four processes in a bridge visual analytical system for the US Department of Transportation and discuss their roles and utilities in real-life scenarios.