Why Knowledge Visualization
- Find out why visualizing knowledge is a crucial, yet emergent, application of the visualization field.
- See sample application areas
- Learn about the different knowledge representation formats
- Build up your skills in assessing knowledge visualization quality
The term Knowledge Visualization is a provocation, as most graphic depictions in this domain contain only information. Nevertheless, they strive to convey more than just simple facts or numbers: Knowledge visualization is about giving concrete form to abstract thought; more specifically to capture insights, experiences, perspectives, even enable skill building:
Knowledge Visualization can help to:
- visualize for your self what you know (and don't know)
- understand what others know
- see how to find knowledge
- learn what others have learned
- structure your thoughts more clearly
- plug into a team's collective wisdom.
But, knowledge visualization is not an easy task. It requires not only domain knowledge but also knowledge about the target group, and about didactic approaches to visualizing knowledge. These issues will be discussed in this module.
The emerging field of knowledge visualization examines the use of visual representations to improve the management of knowledge on all levels (personal, interpersonal, team, organizational, inter-organizational, and societal). Knowledge visualization designates all graphic means that can be used to construct, assess, measure, convey or apply knowledge (i.e., complex insights, experiences, methods, etc.). Beyond the mere transport of information or facts, people who employ knowledge visualization aim to create, assess, reference or transfer insights, experiences, attitudes, values, expectations, perspectives, opinions and predictions, and this in a way that enables someone else to re-construct, remember, find or apply these insights correctly. Examples of knowledge visualization in this understanding are insightful graphic formats such as heuristic sketches (e.g. the ad-hoc, joint drawings of complex ideas in meetings), conceptual diagrams (such as Porter’s Five Forces diagram), visual metaphors (such as an iceberg visualization distinguishing implicit and explicit forms of knowledge), or knowledge maps (such as a landscape of in-house experts).
These graphic formats capture not just (descriptive) facts or numbers, but contain also prescriptive and prognostic insights, principles, basic assumptions and relations. They are used as communication devices in order to trigger sense making activities and to motivate viewers to re-construct meaning. Thus, the ‘what’ (object), the 'why' (purpose), and the ‘how’ (methods) of knowledge visualization differ from information visualization.
Generally speaking, the field of knowledge visualization examines the use of visual representations to improve the creation and transfer of knowledge between at least two people. Knowledge visualization thus designates all graphic means that can be used to construct and convey complex insights. Beyond the mere transport of facts, knowledge visualization aims to transfer insights, experiences, attitudes, values, expectations, perspectives, opinions and predictions, and this in a way that enables someone else to re-construct, remember and apply these insights correctly. Examples of knowledge visualization formats are complex, reasoned and often theory-driven conceptual diagrams (such as Gartner’s magic quadrants or hype curve, Michael Porter’s five forces chart or Nonaka’s SECI matrix, see Nonaka et al., 2000), concept maps (such as Allen Novak’s concept mapping method, see Lansing, 1998), interactive visual metaphors (such as an iceberg of organizational culture or a personnel selection funnel), or knowledge maps (such as Roche’s knowledge application map of the new drug approval process, see Wurman, 1996, p. 172). It seems justified to refer to these graphic formats as knowledge visualizations as both their content and their format are distinct from that of regular visual depictions. In terms of their content, they capture not just (descriptive) facts or numbers, but rather (prescriptive and prognostic) insights, principles and relations. In terms of format, knowledge visualizations rely on indirect communication that triggers sense making activities in the viewer and motivate him or her to complete the picture him- or herself. Thus, the ‘what’ and the ‘how’ of knowledge visualization differs from information visualization, these differences are further described in the following section.
Differences between Knowledge Visualization and Information Visualization>/>>/>
A related field and precursor to knowledge visualization is information visualization. Information visualization is a rapidly advancing field of study both in terms of academic research and practical applications (Bertin, 1974; Card et al., 1999; Chen, 1999a; Spence, 2000; Ware, 2000) . Card et al. (1999) define information visualization, as "... the use of computer-supported, interactive, visual representations of abstract data to amplify cognition ". This definition is well established and represents a broad consensus among computer scientists active in this field. What is still missing in the current literature, however, is a systematic discussion on the potential of visualizations as a medium for the transfer of knowledge as well as the integration of non-computer based visualization methods, as architects, artists, and designers use them. Information visualization and knowledge visualization are both exploiting our innate abilities to effectively process visual representations, but the way of using these abilities differs in both domains: Information visualization aims to explore large amounts of abstract (often numeric) data to derive new insights or simply make the stored data more accessible. Knowledge visualization, in contrast, aims to improve the transfer and creation of knowledge among people by giving them richer means of expressing what they know. While information visualization typically helps to improve information retrieval, access and presentation of large data sets – particularly in the interaction of humans and computers – knowledge visualization primarily aims at augmenting knowledge-intensive communication between individuals, for example by relating new insights to already understood concepts, as in the case of visual metaphors. This visual communication of knowledge is relevant for several areas within knowledge management, as described below.
Knowledge Visualization helps to solve several predominant, knowledge-related problems in organizations:
First, the omnipresent problem of knowledge transfer (or rather knowledge asymmetry and how it can be overcome by transfer). Knowledge visualization offers a systematic approach how visual representations can be used for the transfer of knowledge in order to increase its speed and its quality. The transfer of knowledge occurs at various levels: among individuals, from individuals to groups, between groups, and from individuals and groups to the entire organization. At each of these levels, knowledge visualization can serve as a conceptual bridge, linking not only minds, but also departments and professional groups. Gupta and Govindarajan (2000) have examined knowledge transfer in organizations and they have found that one key issue is how recipients not only acquire and assimilate but also use knowledge (Cohen and Levinthal, 1990) . To do so, knowledge must be recreated in the mind of the receiver (El Sawy et al., 1997) . This depends on the recipient’s cognitive capacity to process the incoming stimuli (Vance and Eynon, 1998) . Thus, the person responsible for the transfer of knowledge not only needs to convey the relevant knowledge at the right time to the right person, he or she also needs to convey it in the right context and in a way that it can ultimately be used. To achieve theses tasks, text and IT-based methods can be employed (e.g., discussion boards, databases, corporate directories, intelligent agent software, etc.). However, the capacities of our visual channel are rarely fully exploited in these applications (be it as an interface to make knowledge accessible or as a way structure the documented or referenced knowledge itself). In this context, visualization can also facilitate inter-functional knowledge communication, as the communication between different stakeholders and experts with different professional backgrounds is a major problem in organizations. Knowledge visualization offers solutions to solve this problem mainly by making differing basic assumptions visible and communicable and by providing common contexts (visual frameworks) that help to bridge differing backgrounds.
As a second application area within knowledge management, knowledge visualization offers great potential for the creation of new knowledge, thus enabling innovation. Knowledge visualization offers methods to use the creative power of imagery and the possibility of fluid re-arrangements and changes. It enables groups to create new knowledge, for instance by use of heuristic sketches or rich graphic metaphors. Unlike text, these graphic formats can be quickly and collectively changed and thus propagate the rapid and joint improvement of ideas.