Knowledge Management Challenges and Solutions to Organizational Knowledge Management in KBMS

The evolution of Knowledge-Based Management System (KBMS) from being limited to only a selected number of taxonomies or approaches to supporting a greater number and versatility of roles continues to expand the versatility of these systems (Faucher, Everett, Lawson, 2008). The transition of defining data elements as part of a SQL-based data structure to being integral to knowledge-based and role-based knowledge models is a current trend (Bellinger, Castro, Mill, 2010). The challenge going forward is to streamline the transformation of data and information into knowledge that can be contextually captured and used in a wider variety of scenarios than is possible given the constraints of these systems today (Grant, Grant, 2008)

Analysis of the Current KBMS Platforms and Architectures

The continual challenges of categorizing explicit...

Tacit knowledge resists the defining of parameters and is the most difficult to capture, (Grant, Grant, 2008). Explicit knowledge has been shown to be easier to capture, yet often lacks context from a strategic standpoint (Faucher, Everett, Lawson, 2008). Reconciling each of these sources of knowledge while enabling technological platforms that can scale to meet role-based needs is forming a new area of KBMS system development and use. No longer concentrating on how to use capture explicit and tacit knowledge the current generate of KBMS systems looks to define constraint-based modeling approaches to determine the optimal path through data (Bellinger, Castro, Mill, 2010). In addition, the use of rules-based modeling techniques that allow for taxonomies to be created literally by role…