An Ontology-Based Collaborative Knowledge Management Network to Enhance the Reusability of Inter-Organizational Knowledge

By Leung, Nelson K. Y.; Lau, Sim Kim et al. | Communications of the IIMA, January 2009 | Go to article overview

An Ontology-Based Collaborative Knowledge Management Network to Enhance the Reusability of Inter-Organizational Knowledge


Leung, Nelson K. Y., Lau, Sim Kim, Fan, Joshua, Communications of the IIMA


INTRODUCTION

In the past two decades, much effort has been spent on integrating heterogeneous information systems. This integration of information systems is essential to allow systems of different characteristics to communicate cooperate, exchange, and to reuse knowledge and services with one another. In the current Internet era, a transaction cannot be completed without accessing data, information, knowledge and services from third party website or information system. For instance, when a customer shops in an online store, the customer may wish to seek comments on the product quality from an external forum website. When the product is purchase, the online store will need to contact a financial institution for payment verification and confirmation. Then a delivery service provider is contacted to handle the delivery or shipment. In this example, a simple transaction involves interoperation and coordination of three heterogeneous information systems. This complexity will increase many fold in real-life practical transactional operation.

The concept of ontology is first applied by artificial intelligence researchers in intelligence system development to share and reuse knowledge. Ontology as a branch of philosophy dealing with the science of what is, the kinds and structures of objects, properties, events, processes and relations in every aspect of reality (Smith, 2003). It is further elaborated as a system of categories which accounts for a certain vision of the world (Guarino, 1998). The term, ontology, is later adopted by artificial intelligence community and Tom Gruber's definition, "ontology is an explicit specification of a conceptualization", has been widely accepted within the community (Gruber, 1993), in which a conceptualization is an abstract, simplified view of the world that we wish to represent for some purpose. Borst (1997) refines Gruber's definition by labelling ontology as a formal specification of a shared conceptualization. Based on Gruber's and Borst's definitions, Studer, Benjamins and Fensel (1998) make the following two conclusions: 1) an ontology is a machine-readable specification of a conceptualization in which the type of concepts used and the constraints on their use are explicitly defined, and 2) an ontology should only capture consensual knowledge accepted by large group of people rather than some individual. By representing knowledge with representational vocabulary in terms of objects and their interrelated describable relationships, inference engine and other intelligent programs will be able to understand the semantic of knowledge in the knowledge base.

Recent growth in the Semantic Web further amplifies importance of ontology. The Semantic Web is extension of the current Web, in which web content is represented in a structural form within ontologies by a finite list of vocabularies and their relationships (Berners-Lee et al., 2001). The role of ontology is to enable computer program, software agent and search engine to understand the semantics of web documents, thus making it possible for them to process the web content. Ontology also provides shared understanding of a domain to overcome differences in terminology from various sources (Antoniou & Harmelen, 2004).

It is impractical to expect each individual and organization to agree on using one or a small set of ontologies (de Bruijn et al., 2006). The adoption of such an approach is difficult. On one hand, it is a non-trivial task to define and maintain a large globally-shared and agreed ontology. On the other hand, this globally-shared ontology may hinder a system from reflecting its actual business requirements due to the constraints imposed in the ontologies such as the terminologies and relationships (Leung et al., 2007). Other researchers, such as Berners-Lee, Hendler and Lassila (2001), state that a large number of small domain-specific ontologies developed by communities, organizations, departments or even individuals are the likely scenario. …

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