A Conceptual Model of a Knowledge Warehouse - Enterprise Information Systems Design, Implementation and Management: Organizational Applications - page 149

regard, understanding the different aspects of in-
formation and knowledge is important, particularly
in light of globalization, ubiquitous computing,
and prevailing knowledge-centric views of the
firm (Prusak, 2001). However, the distinction
between knowledge and information is not always
clear and frequently both are discussed as if they
were one and the same thing.

This paper focuses on integrating KM per-
spectives within existing DW conceptual mod-
eling methodologies, which deal mainly with
operational information. Considerable research
into DW systems is being carried out and major
theories about DW design methodologies are be-
ing developed (e.g. Adamson & Venerable, 1998;
Giorgini et al., 2005; Guo et al., 2006; Holten,
2003; and Kerschberg, 2001). However, research
into KM systems has not yet evolved sufficiently
to have developed systematic, sustained design
methodologies, particularly in regard to applying
knowledge aspects into information systems (IS)
(Jongho et al., 2006). In this paper I present a
methodology for modeling a KW, encompassing
KM in relation to stakeholders, business processes
and various organizational IS.
The paper is organized as follows: in section
2 the theoretical background of KM, DW, and the
linkage between the disciplines are discussed. In
section 3, the KW concept is presented, followed
by its conceptual modeling entitled Knowledge
Warehouse - Conceptual Modeling (KW-CM)
in section 4. Finally, section 5 concludes and
discusses future research directions. Throughout
the paper the KW-CM concepts are demonstrated
with a DW example which handles information
regarding customer product usage.

“Knowledge management has inspired a shift from
a transaction to a distributed knowledge manage-
ment (DKM) perspective on inter-organizational
information processing. […] Each player in
the network acquires specific knowledge from
other players for decision support.” (Pedersen
& Larsen, 2001, p. 139).

According to Stenmark (2002), knowledge is
considered tacit while information is explicit and
tangible. Knowledge practices involve reason-
ing about information and data for leveraging
performance, problem-solving, decision-making,
learning and teaching (Adamson & Venerable,
1998). In my proposed DW conceptual model I
adopt Newell's argument (1981):

“If a system has (and can use) a data structure
which can be said to represent something (an
object, a procedure, whatever), then the system
itself can also be said to have knowledge, namely
the knowledge embodied in that representation
about that thing.” (p. 2)

bAckground

The nature of knowledge and its representation
have long been studied in the field of Artificial
Intelligence (AI). Newell (2002), for example,
realized that a structured symbolic form cannot
solely represent knowledge; knowledge requires
both structure and process representations. In ad-
dition, although knowledge is an abstract concept,
a particular “piece” or “facet” of knowledge must
be coupled with some formal level of representa-
tion to create a sufficiently viable view to justify
regarding it as belonging to the knowledge level.
In this spirit, the proposed KW-CM exhibits the

Prusak (2001) claims that one of the chal-
lenges facing organizations today is managing
knowledge that cannot be digitized, codified, or
easily distributed. The DW conceptual model
that is presented in this paper also deals with a
decision-maker interface on a collaborative in-
formation technology that might connect various
stakeholders during decision-making processes
and foster sharing that kind of knowledge, that
resemble tacit knowledge of decision makers.