By Bain McKay
In the first two articles we discussed the technology components in the new generation of Knowledge Management technology that can unleash the power of knowledge trapped within documents that litter our corporate networks in dead document pools. In this, the third and final article of the series, I'll list some typical applications of the new generation of Knowledge Management technology. We'll discuss the new and powerful concept of active-reflexive data where the data actively, autonomously, and intelligently works for you under the covers. There it leverages details and dynamic associations as they form, facilitating knowledge churn. And we'll address an iconographic drag and drop user-customizable applications interface that users can leverage to automatically assemble their own knowledge applications from knowledge components and semantic operators. This will allow them to solve their specific problems on a timely basis.
Typical Knowledge Management applications
There are many applications that can be simplified significantly using the new Knowledge Management architecture. There are also many applications that weren't possible or scalable under the old information paradigm or even first generation Knowledge Management technology. Examples include the following:
- Managing corporate IQ by facilitating corporate plasticity;
- Automatic assistance in building and managing best-teams;
- Leveraging your experts through expert Knowledge Management and research workstations;
- Mentoring the learning process of tomorrows experts;
- Capturing, monitoring, and leveraging best practices;
- Facilitating knowledge-enhanced e-business transactions through SOAP XML;
- Reading and leveraging corporate cultures and expertise in corporate merger opportunities;
- Using semantic convergence to capture, monitor, and evaluate conformance audits.
Knowledge churn: leveraging infoglut to maintain knowledge currency
Experience has shown that knowledge portals fall into disuse where automated information churn is not present. Churn creates information entropy that generates new knowledge through dynamic cross-document semantic component associations. These dynamic associations, through data reflexivity, provide self-activating knowledge association schemas as knowledge signatures that rebind on significance into new and enhanced kThreads. These can be automatically published to users based on their profiles, knowledge publishing, and routing policies accordingly.