Ontology-Based Competency Management: Infrastructures for the Knowledge Intensive Learning Organization

Learning activities can be considered the final outcome of a complex process inside knowledge intensive organizations. This complex process encompasses a dynamic cycle, a loop in which business or organizational needs trigger the necessity of acquiring or enhancing human resource competencies that are essential to the fulfillment of the organizational objectives. This continuous evolution of organizational knowledge requires the management of records of available and required competencies, and the automation of such competency handling thus becomes a key issue for the effective functioning of knowledge management activities. This chapter describes the use of ontologies as the enabling semantic infrastructure of competency management, describing the main aspects and scenarios of the knowledge creation cycle from the perspective of its connection with competency definitions. Introduction and Background The “Semantic Web” vision described by Berners-Lee, Hendler, and Lassila (2003) has recently fostered research on the use of formal ontologies to support “intelligent” behaviors for a variety of Web applications. These applications include Web-based learning in a broad sense, which is commonly referred to as “e-learning” (Lytras, Tsilira, & Themistocleous, 2003). Nonetheless, the perspective of most of those current applications does not consider organizational needs as the essential driver for the elaboration and delivery of learning activities, but focuses on other aspects regarding technical, social, or usage issues from the perspective of the individual learner or informal communities of learners (Anderson & Whitelock, 2004). An organizational perspective to Semantic Web-enabled e-learning should focus on the role of learning activities in the broader framework of organizational learning (i.e., on providing a semantic account to existing learning processes). But in addition, the implications of the semantic approach to organizations should be explored as a source of new ideals and business designs for learning organizations (Örtenblad, 2001). According to this latter view, the Semantic Web can be considered as the enabler for a new model of a semantic learning organization (SLO) in which ontologies are the technological backbone for intelligent activities and semantics-enabled artifacts. A first step toward the definition of the concept of SLO is the analysis of the essential roles of ontologies in organizational learning. Since learning can be considered as an outcome of the need to acquire new competencies, it is worth first sketching the main components that surround such activities. Figure 1 provides an abstract, idealized view of such components. E-learning can be considered an important component of the knowledge management (KM) function, as described by Wild, Griggs, and Downing (2002). In fact, even some architectural guidelines for this integrated view have been described elsewhere (Metaxiotis, Psarras, & Papastefanatos, 2002), and the use of reusable learning objects in that context has also been analyzed recently (Lytras, Pouloudi, & Poulymenakou, 2002). This perspective puts an emphasis on Web technology-based learning activities inside the organization as enablers of knowledge acquisition activities. In consequence, e-learning becomes part of a more complex organizational conduct, in which lacks of required competencies trigger the search for appropriate contents or activities (i.e., learning objects), in an attempt to acquire knowledge and abilities that fulfill the contingent or strategic need. It should be noted that this approach does not preclude that other kinds of useful informal or incidental learning take place inside organizations (Matthews, 1999), but rather complement them with a more organizational goal-directed activity. In fact, recommender systems for exploiting employee interests like the one described by Lindgren, Stenmark, and Ljungberg (2003) could be built as a complement within the architecture described, also taking advantage of the richness of the underlying ontological structures. As illustrated in Figure 1, the process of acquisition (usually) starts from a business need emanated from the context of the organization, or eventually from strategic management (Rainer & Kazem, 1995). Such needs trigger the process of assessing if the organization is in place to deal with them. Such assessment is commonly referred to as knowledge gap analysis (Sunassee & Sewry, 2002) and essentially consists on matching the competencies required for the incoming needs with the available ones. Such competency management facilities are usually part of the human resources function (Soliman & Spooner, 2000), but this is not relevant for our present discussion. If the result is not satisfactory, the process of searching for available resources should start. This process may entail the selection of learning objects in external or internal repositories and the composition and delivery of the appropriate learning activities. After these activities take place, some kind of assessment would eventually end up with an update of the registry of available competencies. Finally, the newly acquired competencies could change the position of the organization to offer services or products, this way closing the “knowledge acquisition loop. ” The cycle depicted in Figure 1 can be expressed in terms of knowledge management (KM) activities and products. According to the recent Holsapple and Joshi (2004) ontology of KM, competences can be considered as capabilities attributable to processors of knowledge representations (KR), and the final learning activities can be considered as a specific type of knowledge manipulation activity (KMA), consisting on knowledge acquisition or eventually, transformation. Furthermore, processors are considered to Figure 1. The competency-guided organizational learning cycle have some capabilities, which are the focus of analysis in this chapter. This direct mapping of the essential concepts described in this chapter and H&J; ontology of KM enables an effective integration of ontology-based KM and organizational e-learning, providing a concrete mean to the integration framework described by Sicilia and García (2004). This will be the point of departure for the rest of the discussion provided in this chapter. In this chapter, an organizational view of learning processes enabled by Semantic Web technologies is provided, and the essential cornerstones for such semantic learning organization” are considered to be competencies and learning objects. The discussion focuses on competency management and its relationship to the description of learning concepts. Concretely, the second section provides an overview of existing work in ontologies and schemas for competence description. The third section deals with the use of ontological schemas to assess “knowledge gaps,” in terms of the “difference” between required and available competencies. Then, the connection of such knowledge gap with learning object metadata is described in the fourth section. Finally, some conclusions and a future outlook are provided in the fifth section. Existing Schemas and Ontologies for Competency Description Previous research and standardization activities have resulted in a number of data schemas aimed at describing competences. Among them, the competency format specified by the HrXML consortium (Allen, 2003) is of a special relevance for practical purposes, since it is the result of an industrial effort in the direction of interchanging data about competencies in a common format. Competencies in HrXML are defined through XML fragments like the following one, extracted from Allen (2003): <Competency xmlns="http://ns.hr-xml.org" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://ns.hr-xml.org Competencies.xsd"