State of the Art in Semantic Organizational Knowledge

Introduction

Semantic organizational knowledge refers to the Semantic Web and Linked Data technologies that are applied to the principles and procedures of organizational knowledge. The aim of this chapter is to present the state of the art research in semantic organizational knowledge. Originally, organizational knowledge is the ability of employees of an organization to perform tasks given the collective understanding of a particular context. As human knowledge comes in many forms and shapes, previous research conducted by Nonaka (2007, chapter 3), Choo (1996) and Spender (1993), has identified the existence of several types of knowledge in organized contexts including explicit knowledge, tacit knowledge, cultural knowledge and embedded knowledge. Explicit knowledge is intuitive, based on experience, intractable and refers to knowledge known as “know-how”. It was originally defined by Polanyi (1958). The popular view of this type of knowledge is a form of knowledge encoded in organizational practices, procedures and routines. It is also transmittable in formal language as clear facts, propositions and symbols. Tacit knowledge known as “know-what”, is easy to identify, store, retrieve and disseminate. Cultural knowledge refers to being familiar with various cultural characteristics, including history, moral values, belief systems, history, and social norms. In contrast, embedded knowledge, a substantial part of organizational knowledge, is formal or informal knowledge that is locked in archives, processes and internal practices waiting to be extracted. The essence of this knowledge, either individual or collective, is often perceived as a dynamic array of experiences, values, contextual information and expert insights. When it is individual, knowledge shows an individual's ability to demonstrate judgment in a particular situation. In contrast, collective knowledge initiatives in an organization consist of creating and sharing knowledge for improving business and increasing productivity. These initiatives may also expand externally over time and include partners and customers. From this perspective, knowledge becomes an organizational asset that can be managed, shared with partners or provided as a service to others. According to recent research, the Semantic Web, an extension of the current Web (Berners-Lee, 1999; May 2001), (Decker, 2000) and its related Linked Data concepts and techniques appear to be appropriate for solving issues of knowledge acquisition, documentation, transfer and sharing/distribution in an organizational context. In fact, these concepts rely heavily on Resource Description Framework (RDF) and Ontology. 1) The popular RDF model and syntax is a World Wide Web Consortium (W3C) recommendation in February 1999 (Heflin, 2001). An ontology provides an agreed understanding of an organization domain knowledge that rests on a common vocabulary. More precisely, an ontology defines the meaning of the terms in that vocabulary together with their inner relationships (De Araújo, 2015; Chandrasekaran et al., January 1999). It plays a central role in enabling the processing and sharing of knowledge within an accepted domain. Originally, the concept of ontology was created in the branch of philosophy that studies being or existence, the kind of things that exist. Then, the term was co-opted by Artificial Intelligence researchers to represent computational models for automated reasoning. A widely accepted and interesting technical definition of an ontology that still stands in computer science is that “an ontology is an explicit specification of a conceptualization” (Gruber, 1993, p. 1).