Knowledge Sharing for Improved Decision Making



Knowledge Sharing for Improved Decision Making

Introduction

The human brain can perform different heuristics and reasoning approaches which involve everyday experiences and theoretical knowledge. Human brain has the capabilities to combine common sense, previous experiences, and existing data to make important managerial decisions. Human mind can also use indirect knowledge which is in the form of rules to explore new knowledge. Moreover, previous statistics or data can also be mined to predict the future. In order to do decision making just like humans, not only organized data is required but also the data should be presented in such a format that it can be efficiently processed and can be easily used in the reasoning process (Bramblett, 2007, pp. 170-177).

Therefore, database researchers are focusing more on exploring new techniques of storage, managing and retrieval of data and knowledge from a repository which has been acquired from various sources. Only having a repository of data or efficiently organizing the data cannot guide decision makers or management to make accurate decisions as a human can do. The best approach is to integrate and manage the data in the form of knowledge.

A knowledge warehouse can be thought of as an "information repository" which can store a variety of different views of knowledge coming from different sources, in different formats applicable in different areas. In order to stream line the concept of embedding Artificial Intelligence techniques and knowledge warehouse it is very important to enhance, and reorganize the knowledge management process (Efraim, 2009, pp. 23-30).

In this research paper, the knowledge management model is discussed by considering how to modify it, so it can help knowledge creation, refinement, indexing, dissemination and evolution in an efficient and reliable way. The authors have a goal to enhance the knowledge management process which will be the base of building expert warehouse. To achieve this, the authors are trying to refine the existing knowledge management layers which were introduced by Larry Kerschberg:

This research is organized as follows:

Section 2 refers to related work.

Section 3 refers to the problem definition.

Section 4 refers to Knowledge management layers and transformation functions.

Section 5 concludes the paper with future work.

Related Work

It is difficult to define knowledge precisely, it can be considered as broader, deeper or detailed understanding of any concept coming from a source.

When some actionable activity is added in an information process it makes it knowledge; that actionable activity may be in the form of a context. In short updating or enhancing information changes it to knowledge. Knowledge provides a multi dimensional view of information. For example, the knowledge about student's annual report can be viewed by considering multi dimensional variables such as financial support, social status, health condition, teaching facilities, academic environment and many others. These variables or data can be mined to extract knowledge (Lyer, 2002, pp. 143-161).

To achieve this, recently many researchers working on data warehousing, knowledge warehousing areas have made efforts to get successful quality results by either presenting different architectures or tools for integrating data and ...