Knowledge visualization, "the use of visual representations to transfer knowledge between at least two persons" (Burkhard and Meier, 2004), aims to improve the transfer of knowledge by using computer and non-computerbased visualization methods complementary. Examples of such visual formats are sketches, diagrams, images, objects, interactive visualizations, information visualization applications, imaginary visualizations, stories. While information visualization (IV) concentrates on the use of computer-supported tools to derive new insights, knowledge visualization (KV) focuses to transfer insights and to create new knowledge in groups. Beyond the mere transfer of facts, knowledge visualization aims to further transfer insights, experiences, attitudes, values, expectations, perspectives, opinions, and predictions by using various complementary visualizations. Knowledge Visualization has it's roots in Visual Communication, Communication Sciences, Visual Perception and Knowledge Management, where it is a key-issue to make knowledge visible so that it can be better identified, accessed, shared, discussed, applied, or generally be managed.

Contents

1 Knowledge visualization framework 2 Towards a knowledge visualization model 3 Knowledge visualization references 4 Further reading 5 Related research areas 6 Links

Knowledge visualization framework

Figure 1: The Knowledge Visualization Framework (Copyright: Remo Burkhard)

The Knowledge Visualization Framework consists of four perspectives that need to be considered when creating visual representations that aim to transfer and create knowledge: A function perspective answers why a visualization should be used, a knowledge type perspective clarifies the nature of the content, a recipient type perspective points to the different backgrounds of the recipient/audience, and finally the visualization type perspective structures the main visualization types according to their individual characteristics. The framework is described in Burkhard (2004b) and Burkhard (2005); a modified version of the framework is described in Eppler and Burkhard (2005).

Towards a knowledge visualization model

Figure 2: The Knowledge Visualization Model with a sender, a recipient and complementary visualizations as a medium. These three parts are all interlinked in an interaction and communication loop. (Copyright Remo Burkhard)

The Knowledge Visualization Model introduces the salient features that need to be considered when complementary visual representations are used to transfer or create knowledge.

The Knowledge Visualization Model (Burkhard, 2005) is grounded in findings from related Knowledge Visualization Research. See the related references for this point. The model describes inter- and intrapersonal iterative processes: The process starts with a sender who wants to transfer some of his knowledge (knowledge) to a recipient. His mental model of this knowledge (mental model sender) is being externalized into various explicit and complementary visual representations, which can be divided into three sub processes (1,2,3) following a temporal sequence: First, the sender needs to get the attention (1) of the recipient, for instance by using a provocative image. Second, the sender needs to illustrate the context (2), provide an overview (2), and present options to act (2). Only then the sender can point to selected details (3), which ideally happens in a dynamic dialog with the recipient (D), who re-constructs (C) similar knowledge (Knowledge') with these complementary visualizations and an own mental image (mental model recipient). But due to different assumptions, believes, or backgrounds, inferences and misinterpretations can occur (E), which can lead to a failure of the knowledge re-construction. In this process, the sender iteratively refines or adds further visual representations (F), until the knowledge transfer process was succesful.

Knowledge visualization references

• [1] Burkhard, R., 2005, "Towards a Framework and a Model for Knowledge Visualization: Synergies between Information and Knowledge Visualization", in: Tergan and Keller (eds.) Knowledge and information visualization: searching for synergies, Heidelberg / New York, Springer Lecture Notes in Computer Science, [to appear].
• [2] Burkhard, R. and Meier, M., 2005, "Tube Map Visualization: Evaluation of a Novel Knowledge Visualization Application for the Transfer of Knowledge in Long-Term Projects", Journal of Universal Computer Science, (Special Issue Business Process Oriented Knowledge Infrastructures), [to appear].
• [3] Eppler, M. and Burkhard, R., 2005, "Knowledge Visualization", Encyclopedia of Knowledge Management, Idea Group, [to appear].
• [5] Burkhard, R., 2004b, "Learning from Architects: The Difference between Knowledge Visualization and Information Visualization", in: Eigth International Conference on Information Visualization (IV04), London, July.
• [6] Burkhard, R., 2004c, "Visual Knowledge Transfer between Planners and Business Decision Makers", in: Van Leeuwen and Timmermans (eds.) Developments in Design & Decision Support Systems in Architecture and Urban Planning, Eindhoven, Eindhoven University of Technology, 193-208.
• [7] Burkhard, R. and Meier, M., 2004, "Tube Map: Evaluation of a Visual Metaphor for Interfunctional Communication of Complex Projects", in: Proceedings of I-KNOW '04, Graz, Austria, June 30 - July 2, 449-456.
• [8] Börner, K., Chen, C., 2002, Visual Interfaces to Digital Libraries, Lecture Notes in Computer Science, Springer-Verlag, Heidelberg.
• [9] Chen, C., 2003, Mapping Scientific Frontiers: The Quest for Knowledge Visualization, Springer, London.
• [10] Eppler, M. (2004). Facilitating Knowledge Communication through Joint Interactive Visualization. Journal of Universal Computer Science. 10(6), 683-690.
• [11] Horn, R.E., 1998, Visual Language: Global Communication for the 21st Century, MacroVU Press, Bainbridge Island (WA)
• [12] Snowden, D., 2000, "The Art and Science of Story or Are You Sitting Uncomfortably?" Business Information Review.
• [13] Tufte, E.R., 1997, Visual Explanations: Images and Quantities, Evidence and Narrative, Graphics Press, Cheshire (CT).

Further reading

Additional references that are important to the field of knowledge visualization. The list is based on the definition of knowledge visualization (Eppler and Burkhard, 2005).

• Bauer, M. and Johnson-Laird, P. (1993). How diagrams can improve reasoning. Psychological Science. 4 (6), 372-378.
• Bertin, J., (1974). Graphische Semiologie. Diagramme, Netze, Karten; Walter de Gruyter, Berlin.
• Blackwell, A.F., Green, T.R.G. (1999) Does Metaphor Increase Visual Language Usability?. Proceedings of the 1999 IEEE Symposium on Visual Languages VL’99, 246-253.
• Card, S. K., Mackinlay, J. D., Shneiderman, B. (1999). Readings in Information Visualization; Using Vision to think; Morgan Kaufmann, Los Altos, CA.
• Chen, C. (1998). Bridging the Gap: The Use of Pathfinder Networks in Visual Navigation; Journal of Visual Languages and Computing, 9 (3), 267-286.
• Chen, C.(1999a). Information Visualisation and Virtual Environments; Springer, London.
• Chen, C. (1999b). Visualizing Semantic Spaces and Author Co-Citation Networks in Digital Libraries; Information Processing and Management, 35 (3), 401-420.
• Chen, C. (2000). Domain Visualization for Digital Libraries; International Conference on Information Visualisation (IV2000), London, England, July 19 - 21, 2000, 261-267.
• Chen, C. (2003). Mapping Scientific Frontiers: The Quest for Knowledge Visualization; Springer, London.
• Chen, H., Houston, A., Sewell, R. R. and Schatz, B. R. (1998). Internet browsing and searching: User evaluations of category map and concept space techniques; Journal of the American Society for Information Science, 49(7), 582-603.
• El Sawy, O. A., Eriksson, I., Carlsson, S. A. and Raven, A. (1997). Understanding the Nature of Shared Knowledge Creation Spaces Around Business Processes: An International Investigation; Paper presented at the Carnegie Bosch Institute Conference on Knowledge in International Corporations, Rome, Italy, 6-8 Nov.
• Eppler, M. (2003) Managing Information Quality. Increasing the Value of Information in knowledge-intensive Products and Processes, Springer, Berlin.
• Eppler, M (2002). Making Knowledge Visible through Knowledge Maps, in: Holsapple, C.W. (Ed.): Handbook on Knowledge Management, Springer, Berlin, 189-206.
• Farah, M. J. (2000). The cognitive neuroscience of vision; Blackwell Publishers, Malden, Massachusetts.
• Fiske, J. (1982). Communication theory; Fiske, J., Introduction to Communication Studies. Methuen, London/New York: 6-24.
• Fox, E., North, C., Wang, J., Abhishek, A., Anil, B. and Supriya, A. (2002). Enhancing the ENVISION Interface for Digital Libraries; Proc. of the second ACM/IEEE-CS joint conference on Digital libraries, ACM Press, Portland, Oregon, USA, 275-276.
• Fox, E. A., Hix, D., Nowell, L. T., Brueni, D. J., Wake, W. C., Heath, L. S. and Rao, D. (1993). Users, User Interfaces, and Objects: Envision, a Digital Library; Journal of the American Society for Information Science, 44 (8), 480-491.
• Glenberg, A. and Langston, M. (1992). Comprehension of Illustrated Text: Pictures Help to Build Mental Models; Journal of Memory and Language, 31 (2), 129-151.
• Horn, R. (1998). Visual Language: Global Communication for the 21. Century; MacroVU, Brainbridge Island, WA.
• Kleiboemer, A. J., Lazear, M. B. and Pederson, J. O. (1996). Tailoring a Retrieval System for Naive Users; Proc. 5th Symposium on Document Analysis and Information Retrieval (SDAIR96), Las Vegas, 1996, 209-216.
• Koffka, K. (1935). The Principles of Gestalt Psychology; Harcourt Brace, New York.
• Kosslyn, S. M. (1980). Images and Mind; Harvard University Press, Cambridge, MA.
• Larkin, J. and Simon, H. (1987). Why a Diagram is (Sometimes) Worth Ten Thousand Words; Cognitive Science, 11, 65-99.
• Lin, X., White, H. D. and Buzydlowski, J. (2001). Associative Searching and Visualization; International Conference on Advances in Infrastructure for Electronic Business, Science, and Education on the Internet (SSGRR01), L’Aquila, Italy, August 6-12.
• Lin, X., White, H. D. and Buzydlowski, J. (2003). Real-time author co-citation mapping for online searching; Information Processing and Management: an International Journal, 39 (5), 689-706.
• Loebbert, M. (2003). Storymanagement - Der narrative Ansatz für Management und Beratung; Klett-Cotta, Stuttgart.
• Mandl, H. and Levin, J. R. (1989). Knowledge Acquisition from Text and Pictures; North-Holland, Amsterdam.
• Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information; Psychological Review, 63, 81-97.
• Novick, L. R. (2001). Spatial diagrams: Key instruments in the toolbox for thought; Medin, D. L., The psychology of learning and motivation. Academic Press, San Diego, CA 40: 279-325.
• Nowell, L. T., France, R. K., Hix, D., Heath, L. and Fox, E. (1996). Visualizing Search Results: Some Alternatives To Query-Document Similarity; Proc. ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR96), Zurich, Switzerland, 67-75.
• Sebrechts, M. M., Vasilakis, J., Miller, M. S., Cugini, J. V. and Laskowski, S. J. (1999). Visualization of Search Results: a Comparative Evaluation of Text, 2D, and 3D Interfaces; Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval, ACM Press, Berkeley, California, United States, 3-10.
• Shepard, R. N. and Cooper, L. A. (1982). Mental Images and Their Transformations; MIT Press, Cambridge, MA.
• Sparrow, J., (1998). Knowledge in Organizations. Sage, Thousand Oaks.
• Spence, B. (2000). Information Visualization; ACM Press.
• Sutcliffe, A. G., Ennis, M. and Hu, J. (2000). Evaluating the effectiveness of visual user interfaces for information retrieval; International Journal of Human-Computer Studies (53).
• Swaab, R.I., Postmes, T., Neijens, P., Kiers, M.H., Dumai, A.C.M. (2002) Multiparty Negotiation Support: The Role of Visualization’s Influence on the Development of Shared Mental Models. Journal of Management Information Systems. 19(1), 129-150.
• Toulmin, S. (1964). The Uses of Argument; Cambridge University Press, Cambridge, UK.
• Tufte, E. (1990). Envisioning Information; Graphics Press, Cheshire.
• Tufte, E. (1997). Visual Explanations; Graphics Press, Cheshire.
• Vance, D. and Eynon, J. (1998). On the Requirements of Knowledge-Transfer Using Information Systems: A Schema Whereby Such Transfer is Enhanced; Proceedings of the Fourth Americas Conference on Information Systems, Baltimore, MD, 632-634.
• Vande Moere, A., Mieusset, K. H. and Gross, M. (2004). Visualizing Abstract Information using Motion Properties of Data-Driven Particles; Proc. of Conference on Visualization and Data Analysis 2004, IS&T/SPIE Symposium on Electronic Imaging 2004, San Jose, CA.
• Ware, C. (2000). Information Visualization: Perception for Design; Morgan Kaufmann, San Francisco.
• Weidenmann, B. (1989). When Good Pictures Fail: An Information-Processing Approach to the Effect of Illustrations; in: Mandl, H. and Levin, J. R. (Eds.). Knowledge Acquisition from Text and Pictures. Elsevier, North Holland.
• Weiss-Lijn, M., McDonnell, J. T. and James, L. (2001). Visualising Document Content with Metadata to Facilitate Goal-Directed Search; Fifth International Conference on Information Visualization (IV01), 71-76.
• White, H. D., Buzydlowski, J. and Lin, X. (2000). Co-Cited Author Maps as Interfaces to Digital Libraries: Designing Pathfinder Networks in the Humanities; IEEE International Conference on Information Visualization (IV00), London, 25-30.
• Worren, N., Moore, K., Elliott, R. (2002). When theories become tools: Toward a framework for pragmatic validity. Human Relations. 55(10), 1227-1250.
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Related research areas

• Information visualization
• Knowledge management
• Knowledge transfer

Links

• http://www.graphicslink.demon.co.uk/IV05/ (First International Symposium on Knowledge and Argument visualization)
• http://www.unisg.ch/org/mcm/web.nsf/wwwPubInhalteEng/CCKV?opendocument
• http://www.knowledgemedia.org
• http://www.vasp.ch
• http://www.idiagram.com/
• http://www.delta7.com/
• http://www.semantic-web.at
• Hodges Health Career - Care Domains - Model
• Sciences Domain Links, inc. Visualization & Diagrams

etc