Knowledge Management Tools : Component Technologies
Introduction :
The internet provides a multitude of vendors promising to transform our business. But , we have to know which approaches should be adopt to examine the component technologies that make up a knowledge management system or suite. The analogy of hi-fi is used where each item has a certain function or purpose.
The multitude of KM system on offer in the marketplace is seen as a composite variation of a number of these component technologies. Firms may decide to buy different component-of-the-shelf or develop their own tools to meet their needs.
Organising knowledge tools
Ontology and Taxonomy
Grubber (1993) defines ontology as “a formal explicit of shared conceptualism”. It helps us on preventing wide variations on understanding or perspective to the same subject. Therefore, we have to developed ‘ontology’ to improve our level of information organization, management, and understanding.
In the context of KM tools, the term ontology is often used interchangeability with taxonomy. To clarify the distinction, it’s important to recognize that an ontology is overall conceptualism whereas taxonomy is a scientifically based scheme of classification. An ontology may have non taxonomic conceptual relationship such as ‘has part’ relationship between concepts. In contrast, knowledge taxonomy generate hierarchical classification of terms that are structured to show relationship between them.
When it comes time to implement ontologies and taxonomies there are three options:
· develop the ontology then develop the supporting taxonomy.
· develop taxonomy and then develop the over-arching ontology
· develop the two in parallel.
Define your scope
The first step in developing the combined ontology and taxonomy is to clearly scope the effort. A clearly defined scope is critical to the success of the effort. The question that can best help shape the scope of the effort is
Links: Online Analytical processing (OLAP) The best known knowledge discovery techniques are online analytical processing (OLAP) and data mining (DM) techniques (Turban et al., 1999)