Formalization of an enterprise ontology based on agents and contexts

• Main Author: Saavedra, Héctor Rodrigo Rubilar
• Publication Date: 2011
• Format: Master thesis
• Language: eng
• Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Download full: http://hdl.handle.net/10400.1/927
• topic: Ontologia; Modelo empresarial; Modelo orientado a agente; Regras; Metodologias

Communication it is a fundamental organizational aspect but not always easy to achieve due to differences between the parts involved (distinct beliefs, backgrounds and needs). Poor communication can lead the organization to several problems like poor resource re-utilization, deficient inter-operability, underutilization of information, among others. These communication problems are translated into information flux problems (we do not use efficiently the information, we do not understand each other and we do not define problems or propose solutions adequately). Addressing these problems its crucial in every organization that understands the value that information has. Ontologies help us solve the previous situations. They provide a common understanding of a conceptualization of the study object so they allow us to model the study object and to describe it using the same language. Enterprise ontologies allow us model an organization like the enterprise using a unambiguous and commonly accepted terminology who define enterprise terms like activity, resource or process with which we can represent enterprise operation and manage information efficiently. Commonly, enterprise ontologies model formal elements of an organization, but since enterprises are composed by parts of different nature, informal elements emerge and create relations and different perspectives with respect to the rest of the enterprise components. This document study an agent based and context aware framework who encompasses both, formal and informal element of the enterprise. This work results on a formalized OWL ontology that will allow us to answer question with information inferred from the model.