Knowledge Maps – Combine knowledges

Hey there, let’s check our knowledge maps.. 


1. Knowledge maps based on skill level of each individual on our group Fourthinks

2. Our Relationship of Knowledge Exchange based on Blog Activities.

3. Our Relationship with our Environment

Knowledge Management in Practice

             In the context of KM, CoPs are generally understood to mean electronically linked communities. Electronic linkage is not essential of course, but since KM arose in the consulting community from the awareness of the potential of Intranets to link geographically dispersed organizations, this orientation is understandable and inevitable. The organization and maintenance of CoPs is not a simple and easy undertaking. As Durham, M. [2004] points out, there are several key roles to be filled, which she describes as manager, moderator, and thought leader. They need not necessarily be three separate people, but in some cases they will need to be.

                 If we create a matrix in which the rows are KM Processes and the columns KM Procedures and Practices, and in which the ordering, top to bottom and left to right is roughly in chronological or developmental order, and we check which process a practice or procedure is primarily designed to serve, the matrix looks like:

                 That matrix reveals several interesting things. Almost everything one does in KM is designed
to help find information and knowledge.However, if we assume that the main goal ofKMis to share knowledge and even more importantly to develop new knowledge, then the Knowledge Audit and the Tags, Taxonomies and Content Management stages are the underpinnings and the tools. It is the knowledge sharing and knowledge creation of one on one communications enabled by expertise locators, and the communal sharing and creation of knowledge enabled by communities of practice toward which KM development should be aimed.

Knowledge “Acts”

                  Shared meanings and purposes as well as newknowledge and capabilities, converge on decision making as the activity leading to the selection and initiation of action.Shared meanings, agendas, and identities select the premises, rules, and routines that structure decision making. New knowledge and capabilities make possible new alternatives and outcomes, expanding the range of available organizational responses [Choo, C., 2002, p. 86]. Choo further proposes that information flows are a central process that bridges knowledge creation and decision making activity. Information flows continuously between sense making, knowledge creating, and decision making, so that the outcome of information use in one mode provides the elaborated context and the expanded resources for information use in the other modes [Choo, C., 2002, p. 85].


                       Information used in one activity that results in new knowledge will, in turn, be used to guide selection of alternatives in future tasks that involve decision making. Codified rules and routines would be relied on to support evaluation of alternatives and selection of action decisions. Choice of alternatives, and decision outcomes then provide the backdrop upon which sense making, or justification, of decision rationale occurs. Such decision rationale, and its associated sense making can then be codified for (re)use in other contexts, applied to future activities that draw on it to create new instances of knowledge.

                     In such decision oriented activity, we have proposed that “what-if ” questions are the dominant type of speech act performed.Support for such scenario predicting questions will demand rich context upon which to apply knowledge of the past and the present to bear on the problem or situation at
hand.We would like to refocus the discussion of knowledge management strategy to the demands of complex, dynamic, contextual, and emergent decision processes. The next section of the paper gives an overview of knowledge management processes, procedures, and practices. Chapter 8 discusses how they are related to decision making.

Conceptualizing Knowledge Emergence

                   The Information Systems literature points to an abundance ofKMstrategies in the category of Computer Mediated Communication (CMC). Such systems provide the infrastructure for enabling the interactions needed for a group’s knowledge synergies and interactive activities [Maier, R., 2002] and may include bulletin boards, electronic meeting/conferencing, or online chat. In this model, the notion of space [Ruhleder, K., 2002], physical or otherwise, is important primarily because the meeting place or system provides an environment that allows for interactions to unfold, at the convenience of individual participants, often asynchronously. Further, such CMC interactions allow for the creation of persistent records [Robins, J., 2002] of the interactions. Chat and other kind of social media transcriptions can be preserved too as another example. To the extent that discourse occurs through such interactions, the dialectics can be archived for future reference and subsequent “reuse.” However, as Hislop, D. [2002] points out, while technology may provide the tools for interaction and communication, the application of technology alone may not be a sufficient condition for sustaining the creation and sharing of knowledge.

                        Generic Decision Support Systems (DSS) that act more like expert systems with the added feature of suggesting decision options are well suited to the Web, and they are proliferating as the Web becomes the ubiquitous information and communication platform for information storage and retrieval, and for interaction as well.The range ofWeb-based DSSs vary in quality fromthemundane (e.g., cosmetics or movie choices) to sophisticated tools such as diagnosing illnesses and suggesting appropriate drug therapies. Especially in the medical domain, DSS systems have taken the burden of calculating dangerous drug interactions from the physician’s shoulders and offer drug suggestions that include cautions about side effects and problems with other prescriptions patients already have. Anyone can useWebMD or Isabel to test his or her own symptoms against the collected wisdom of clinical experts who have contributed to the systems’ “knowledge bases.” Generally, these reputable clinical decision support systems are advised by an independent board of medical professionals, and they rely on the experts’ knowledge in order to make suggestions for conditions and treatment. Other dependable DSSs have used the expertise of meteorologists to predict storms, knowledge of cattle managers to give advice on culling herds, or the know-how of environmentalists on managing water resources. No doubt, these systems will be replaced by others as technology advances, and their capabilities and functionality will increase.