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decision maker. However, Liou (1992) states that as
people are becoming more experienced in
performing a certain task, they are becoming less
aware of cognitive processes involved in
accomplishing that task. Since knowledge
engineering methods and techniques have already
been successfully applied in various areas (e.g. water
resources management (Mikulecký, Ponce and
Toman, 2003) or tourism (Čech and Bureš, 2009)),
the abovementioned problem can also be treated
with the help of these. Therefore, knowledge
acquisition needs to be performed in order to capture
and share the reasoning processes of an expert.
3 METHOD
The paper explores the use of various conceptual
modelling techniques for knowledge acquisition.
The task is to find a framework that will serve two
purposes. First, it will be used to offer a way how to
conceptualize knowledge from the different domains
acquainted from different experts. Second, the
framework would offer the decision maker a
comprehensive pattern for decisions during
biochemical incidents taking into account various
aspects, stakeholders and responsible authorities.
The paper will be divided into two parts. First,
conceptual modelling will be reviewed and selected
conceptual modelling techniques will be presented
in order to find an appropriate tool for transferring
domain knowledge from experts to decision maker
that is responsible for coordinating response
operations. The techniques will be reviewed with
respect to application in knowledge sharing as a part
of knowledge acquisition task. Also, the possibility
to create conceptual models of decision making in
emergency situations caused by biochemical agents
will be considered. Second, the approach taken
during the research dealing with decision support
tools in emergency situations will be presented.
4 CONCEPTUAL MODELLING
As stated by Robinson (2006) conceptual modelling
is concerned with appropriate simplification of a
reality or of a proposed system. Although, there is
not a common consensus of how to define
conceptual modelling, the researchers such as Luo
and Yoshida (2007) or Mandl and Levin (1989)
regard conceptual modelling as a mental tool that
helps to convey thoughts and ideas and thus is often
denoted as a knowledge sharing technique. The
central idea of a conceptual modelling is an
identification of relevant concepts denoted as
entities, objects, things or similar constructs and
their mutual associations known as relations. The
conceptual model is stripped from technological and
implementation details. The purpose of the
modelling and the approach determines logical
pattern and thus what is relevant and what might be
abstracted. The conceptual modelling is often
connected with visualisation techniques. It is argued
for instance by Kosslyn (1980), Mandl and Levin
(1989), or Shepard and Cooper (1982) that visual
representation makes for easier recognition and
recall then merely textual representation.
There are several conceptual modelling
techniques each following a slightly different
purpose and defining special principles and
perspectives that are to be focused on. The
techniques define also the visual representation with
its own notation. However, the majority of visual
representations are based on graphs with nodes and
arcs. The core of the modelling consists of
constructing the visual representation along the
given principles. The simple techniques concentrate
only on specifying names to nodes and arranging
links in between. The advanced conceptual
modelling approaches such as object or ontological
modelling enhance the model by further
specification of nodes and arcs.
In the scope of the research the focus were aimed
at mind mapping, cognitive maps, entity relationship
(ER) modelling, object modelling, ontological
modelling and decision trees.
Mind maps consist of arranging related concepts
around a central key concept. According to Luo and
Yoshida (2007) mind mapping is often used for
learning and brainstorming. Mind maps offer a
structural view of concepts in a certain domain. The
technique is useful in cases when one central
concept can be defined and where there are not
many overlapping and duplications of concepts and
their relations.
Cognitive maps are used for the mental
representation of concepts and causal assertions.
Spicer (1998) reminds that cognitive maps were
originally developed by psychologists and can be
used to support transition of knowledge and
promotion of understand and shared thinking about a
certain problem domain.
ER modelling is primarily employed in logical
design of databases. The technique deals with
entities that can be further extended with attributes
and relations. The relations are interesting especially
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