exists various methods to represent knowledge such as—concept map[15],
knowledge Vee[15], Concept Circle Diagrams[5], SemNet[5], Conceptual
Graphs[19]. After analyzing the concept mapping methodology, we identi-
fied several problems on the basis of the assumptions stated above, and par-
ticularly due to the use of knowledge organizers. In the traditional concept
mapping methodology the relation types (linking words) such as—is-a, for
e.g. are ambiguously used; too many linking words are used to express the
same meaning; the hierarchies are not ordered and not validated. Hence,
the graphical representation is misleading to evaluate concept maps. A crit-
icism of concept mapping methodology is discussed separately in a work-
ing paper, Towards Principled Approach of Concept Mapping[10]. We find
the conceptual graphs approach by Sowa[18] highly instructive and we
plan to make use of this technique for representing scientific knowledge.
Sowa’s approach is sufficiently formal to represent knowledge in precise
terms, and is comprehensive enough to use in several domains of knowl-
edge. Based on the current wisdom in KR, we developed a modeling tool to
undertake the task. The tool is called GNOWSYS (Gnowledge Networking
and Organizing SYStem)[8]. After introducing the model of GNOWSYS,
we introduce the model followed for representing a small domain of biol-
ogy. The purpose of this communication is limited to share the approach
and assumptions followed.
GNOWSYS (Gnowledge Networking and Organiz-
ing SYStem)
While designing the architecture of GNOWSYS, we kept in mind the need
for drawing concept graphs, semantic nets and concept maps. Recently,
several researchers used concept maps[15, 14] and SemNet[4, 5] to en-
hance conceptual learning in the context of science education. Most of
these tools, suggested in the above citations, are essentially drawing tools,
and the maps drawn by the students or experts could not be stored in an
accessible knowledge base. Graphs were stored as separate files, which
makes reusing a component of a graph difficult. Since the graphs were
encoded in a format that is internal to the applications, it is difficult to
compare two concept graphs, made by different applications and remain