Critical Success Factors in the Development of Folksonomy-Based Knowledge Management Tools

Critical Success Factors in the Development of Folksonomy-Based Knowledge Management Tools

Kenneth Owen (Lakehead University, Canada) and Robert Willis (Vancouver Island University, Canada)
DOI: 10.4018/978-1-60960-783-8.ch323

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Introduction

In today’s knowledge economy, companies struggle to find ways to collect, retain and reuse information as efficiently as possible. Control structures found in traditional Knowledge Management (KM) systems are difficult to maintain and require specialized knowledge and training to be effective (Davis, Studer, Sure, & Warren, 2005). Traditionally, knowledge management experts are hired to develop complex hierarchies and ontologies to design systems based on pre-defined information structures (such as categories and relationships). Maintaining these systems and ensuring they continue to match the needs of an organization is a skilled art. If managed poorly, these systems have the potential to miscategorize and lose data. Additionally, overly rigid information structures can hinder the collection of information while overly ambiguous structures can draw information into a virtual black hole.

Recently, a new instrument has appeared in the knowledge manager’s toolbox -folksonomy. Folksonomies represent a nearly diametrically opposite approach to traditional information organization. For example, while ontologies rely on knowledge management experts to develop specific functional definitions, folksonomies impose no preconceived definitions and allow group consensus to reinforce appropriate classifications that emerge organically.

Hierarchies attempt to organize information and give context to data through a branching structure while folksonomies allow for a multiplicity of contexts. Rather than working from the top down to build a structure and then insert data, folksonomies start at the data level and allow communities of knowledge for consumers to apply their own organization, in the form of tags and metadata, to whatever information they see as valuable. “Folksonomies [have allowed] communities of users to build structure on top of content using tags as annotations” (Dubinko, Kumar, Magnani, Novak, Raghavan, & Tomkins, 2006). As metadata grow, the context of the information also broadens and thickens. This process leads to folksonomies adapting to their communities’ needs and offers a flexible strategy for maintaining dynamic information resources: “[S]ystems employing free-form tagging that are encouraging users to organize information in their own ways are supremely responsive to user needs and vocabularies, and involve the users of information actively in the organizational system” (Mathes, 2004).

One of the most frequently observed challenges of the use of folksonomies in knowledge management is the lack of control and structure around the use of tags (Peters, 2006): “A folksonomy represents simultaneously some of the best and worst in the organization of information. Its uncontrolled nature is fundamentally chaotic, suffers from problems of imprecision and ambiguity…” (Mathes, 2004). However, it remains to be determined whether, in scaling down a folksonomy from its traditional global scope (involving millions of contributors) to a size more commensurate with corporate-sized KM solutions, there is enough metadata to make a folksonomy effective.

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