A Concept Mapping Tool to Handle Multiple Formalism

Concept maps are used in a wide variety of disciplines because of their ability to make complex information structures explicit. Concept maps can be used informally or formally -where the graphical "syntax" of the maps is tightly controlled. Both forms are needed. Constraint Graphs is a program in which users can constrain arbitrary graphs to conform to any of a wide variety of graphical formalisms. The Constraint Graphs program is combined with a graphical user interface to yield an interactive concept mapping system, that can transcend informal concept mapping and many concept mapping formalisms. SUMMARY: CONCEPT MAPS AND KNOWLEDGE MANAGEMENT Concept mapping is a simple and intuitive method of representing knowledge in a more flexible and natural form than is possible with other forms of representation such as pure text or strict formalisms (e.g. predicate logic). Concept maps are composed of nodes and arcs connecting the nodes. Nodes represent concepts and are labeled with a short description of the concepts. Arcs represent the relationships among the concept nodes and are usually labeled with a the relationship type. This simple notion leads to very powerful knowledge representation for both human understanding and computer processing. For example, Figure 1 shows a concept map the may be developed by the participants in a decision-making meeting. The visual language used in Figure 1 is a semiformalism called glBIS (Graphical Issue Based Information System). Here, the elliptical nodes represent issues, the rounded-rectangular nodes represent positions taken on the issues, and the rectangular nodes represent arguments. The arcs connecting the nodes are all labeled with relationship types. The decision making process represented in Figure 1 shows a clear and clean structure that would be quite difficult to represent using plain text. The relative linearity of text would obscure the relationships among the individual arguments and the sub-set of positions they related to. To be sure, a two-dimensional table could clearly represent the structure of most of Figure 1 (with the exception of the "standardization" part), but tables quickly become difficult as the complexity of the situation increases. The flexible, two-dimensional structure of the concept map is much more capable of clearly representing complex knowledge structures. Concept maps can not only be used for decision making, but also for design, description, planning, brainstorming, scenario construction, and modeling. Furthermore, if concept maps are used in these ways, they can also serve as easy-to-collect corporate records of these activities. In addition, concept maps can be used in conjunction with hypermedia navigation systems to create "meta-concept maps" -concept maps that can be used to organize and navigate large collections of other concept maps. If the "syntax" of concept maps is restricted (formalized) such that a semantics may be associated with them, then computer programs can be created to process the maps in various ways: for information retrieval, for decision support, and for knowledge-based inference by automated agents. Thus, various forms of concept mapping are useful in industry for representing knowledge for both human understanding and computer support. But the different sorts of concept maps used in different ways may become difficult to handle and support. A central concept mapping "’i ~;..,~ (1~ t:t~:, ~ ̄ l:iy head office .... .~ has ~]eneralizes C--.#~’support -~-~’" standardized repor~d.~.to ..... supports_ / Pnmn=ttPr ~, . .f’~ I we have a I ~;;ouT;;;;, )~=:::~epo.d.~,o . .. ....~,,pr, ort.~---lve./,,ml,ed I "repl.~r~d,.:-to ~ [ budget [