Conclusion Tomake knowledge management KM systems more effective and success- ful, they should support users’ thinking, reasoning and learning to facilitate decision support, problem
Trang 1140 Leung
well-placed online support is essential for effective and efficient learning/ training By the same token, online support can be measured by the type of support offered, the comprehensiveness of support provided, and the way that this support is accessed
From a research point of view, amodel can be built that shows the intervening effects among these six factors contributing to learning effectiveness This chapter certainly has paved the way for constructing such a model, and subsequently conducting in-depth empirical analysis to determine the strength
of these relationships as well as integrative influences on learning/training effectiveness Toward this direction, the measurement variables and their corresponding constructs will have to be developed, refined and validated
Conclusion
Tomake knowledge management (KM) systems more effective and success- ful, they should support users’ thinking, reasoning and learning to facilitate decision support, problem solving and knowledge transfer Particularly, when
KM systems are used in training for personal growth and organizational effectiveness, they should be designed paying more attention to modern learning theories
The review of the learning theory developments indicates that the focus of
learning has been shifting from direct instruction of the objectivism to a more opened and learner centered learning process of constructivism Its implication
to KM system development is that KM systems should provide users shared environments for sustained exploration, problem solving and learning Toward this endeavor, six issues were considered and discussed in the chapter, namely media of representation, complexity, multiple perspective, user control, online support and navigation aids Under each issue, various strategies and imple- mentation methods were proposed, most of which were based on validated learning research as well as successful applications Itis believed that whena
KM systemis built mlime with the six issues, its training effectiveness as well as for other purposes of use will be significantly improved
Overail, this chapter provides invaluable insight into the development of KM
systems in view of the lack of support of learning theories in many KM applications Itshows how the learning principles can be implemented in a KM
Trang 2An Effective Tool for Learning and Training 141
system for effective learning, problem solving and knowledge transfer For further research, empirical study may be conducted to show actual evidence of improvement in learning effectiveness Also, additional issues or strategies may
be continuously identified and explored
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Trang 10Web Service Modeling Framework for ihe Enhanced Data Warehouse 149
Chapter VIII
Krzysztot Wecel
The Poznan University of Economics, Poland
Pawel Jan Kalezynski University of Toledo, USA
Witold Abramowicz The Poznan University of Economics, Poland
Abstract
This chapter presents how Web services architecture can be leveraged to extend an existing system to an open and flexible platform ft reviews crucial issues related to modularization, properties of the Web services,
integration of heterogeneous services and incorporating new services We
describe the modeling framework used, whichis the Web Service Modeling
Framework{WSMPF) As acase we show how the enhanced data warehouse
system was remodeled in order to transform it from a closed solution to
an open Web services-based system called the enhanced Knowledge
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Trang 11150 Wecel, Kalczynski & Abramowicz
Warehouse (eK W) We analyze eKW as a Web service and show how eK W conforms to the eight layers of functionality in Web services We alse speculate about the future of eKW in the semantic web and innovations it can contribute to knowledge management In the semantic Web eDW Should be used as a source of knowledge, hence the name “knowledge warehouse”
Tim Berners-Lee suggested another solution —to create the Web so that itcan
be easily processabie by machines Such a Webis called the semantic Web
(Berners-Lee, Hendler & Lasilla, 2001)
Another issue is making acomputer application accessible through the Web The ultimate vision is that of the Web as a distributed computation device
According to the IBM Web Services Tutorial, “web services are anew breed
of web applications They are self-contained, self-describing, modular appli-
cations that can be published, located, and invoked across the Web” (Leymann,
2001)
The idea we extend in this chapter was originally called the enhanced Data
Warehouse (eDW) (Abramowicz, Kalezynski & Wecel, 2002) As aresponse
to numerous proposals to improve the original concept of data warehousing,
(e.g., Gray & Watson, 1998; Nematietal., 2002), eDW extends the existing
enterprise data warchouse with unstructured information filtered from selected sources on the Web eDW was primarily designed as aclosed system; thatis, only users of a particular data warehouse could take advantage of this sohation
Moreover, eDW was entirely based on internal modules without taking
advantage of other systems According to recently observed trends, we decided to re-engineer the architecture of the eDW system
Trang 12Web Service Modeling Framework for ihe Enhanced Data Warehouse 151
Background
eDW is an agent-based system that allows the automatic filtering of information from the Web to the data warehouse and automatic retrieval of this information through the data warehouse (Abramowicz, Kalczynski & Wecel, 2002) The
overview of the system is presented in Figure 1
Components of the eDW system were divided into two main types: agents and servers Software agents are software entities that carry out some set of
operations on behalf of a user or another program with some degree of independence or autonomy, and in so doing, employ some knowledge or representation of the user’s goals or desires (Grosof & Kephart, n.d.) Inturn, servers are components that are responsible for creating agents, serving as a contact point for agents, and storing the complete knowledge of the eDW agents
The eDW system comprises four main servers:
e Profiling Server —personalizes the data warehouse and discovers the long-term information needs of data warehouse users
Figure i Overview of the enhanced data warehouse (Abramowicz, Kalezynski & Wecel, 2002)
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internet serine = =
and Intranet gents Source Agen KOORNỔ - pm Warebouse
Server promos À Server agents
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Agents Agenis Server
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