01 November 2010

Knowledge Maps – Part II: Knowledge Mapping

   It’s natural to talk about K-maps within Knowledge Representation, and extensively within Knowledge Management, domains in which the process of creating a K-map is known as Knowledge Mapping, shortly K-mapping. In essence that’s what K-mapping is about, creating a K-map, however in literature could be found more elaborated definitions. According to D. Hyerle, K-mapping is “a rich synthesis of thinking processes, mental strategies, techniques and technologies, and knowledge that enables humans to investigate unknowns, show patterns of information, and then use the map to express, build, and assess new knowledge” [1]. Within the same context but from a slightly different perspective, [3] regards it as a “consciously designed communication medium using graphical presentation of text, stories, models, numbers or abstract symbols between map makers and map users”. In the context of K-mapping in organizations, B. Bergeron defines it as the “process of identifying who knows what, how the information is stored in the organization, where it’s stored, and how the stores of information are interrelated” [2]. All the above definitions focus on mapping as a process, knowledge as the object of the mapping process and the context in which it occurs.

    The use of various types of K-maps introduces similar concepts, K-mapping being referred as concept mapping when talking about concept maps or when the granularity of a map is at concept level, mind mapping when the focus is Mind Maps or externalization of mental maps, semantic mapping when discussing about semantic maps, process mapping in the case of process maps, etc. Related concepts stress other aspects of K-mapping referring to different levels of abstraction, for example ontology creation or ontology engineering, in this context ontology mapping referring to the mapping between different ontologies. Same happens in the world of the databases in which data modeling or semantic modeling refers at the creation of a data model, while data mapping refers at the mapping between two structures.

   As stressed before, the various types of K-maps in use introduce their own creational philosophy, which with a little effort could be raised at the state of methodology. K-mapping as a process could be reduced to input, output and what happens in between. As input for a K-map could be used the various types of media content, mental models, knowledge of experts, discussions outcomes or any other sources of information. As knowledge is not always available at our disposal, searching for knowledge, identifying knowledge is quite a time consuming task, especially when knowledge is not indexed, easily accessible or we don’t exactly know what we are searching for. In general we talk about knowledge acquisition, which refers to the process of extracting knowledge, structuring and organization of knowledge. When creating a K-map we are doing extensively knowledge acquisition, essential in the process of learning. In exchange, when we create K-maps on the mental models, we are externalizing our knowledge, transforming the tacit in explicit knowledge, figuring out or better said evaluating what we stored in our brain, grounding of knowledge by finding meanings, formalizing concepts, finding the best formulation, finding new associations, building on previous knowledge, examine beliefs, integrating, mixing and recombining knowledge, identify patterns in knowledge, patterns of thinking, becoming creative, etc. Also these aspects are part of K-mapping, even if they are not so visible in the process, however they are stressed especially during K-mapping. The structuring and organization of knowledge in K- mapping is done in representational form (visualization), translated into spatial organization or simple aggregation of information, in patterns or models of expressions, and here the various types of K-maps are used as a form of expression. Mapping techniques need to be flexible in order to reflect the representational richness of knowledge, they evolve with experience, “the one who maps” learning with time to take advantage of the appropriate type of K-map or pattern. K-mapping is thus an iterative process, a K-map being evolved during several stages, the final outcome being unexpectedly different than the inputs or expected outcomes.

   K-mapping applies to individuals as well as to groups, collaborative or coordinative K-maps involving more complex forms of acquisition, process or visualization, often being involved some forms of negotiation and knowledge sharing from which the output emerges. Collaborative K-mapping seems to be preponderant to the contexts in which the force of the group emerges, mainly economical and scholar organizations, and recently social networks.

References:
[1] M. Jafari, P. Akhavan, A. Bourouni, R. H. Amiri, (2009). A Framework For The Selection Of Knowledge Mapping Techniques. Journal of Knowledge Management Practice, Vol. 10, No. 1, [Online] Available from: http://www.tlainc.com/articl180.htm (Accessed:16 October 2010)
[2] B. Bergeron. (2003). Essentials of Knowledge Management. John Wiley & Sons, Inc. ISBN: 0-471-28113-1.
[3] H. P. Tseng, Y-C. Lin (2008) A Knowledge Management Portal System for Construction Projects Using Knowledge Map. Knowledge Management:
Concepts, Methodologies, Tools and Applications, M.E. Jennex (Ed.). ISBN-13: 978-1-59904-934-2.

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