An enterprise modeling and integration framework based on knowledge discovery and data mining

Abstract

The paper deals with the conceptual design and development of an enterprise modeling and integration framework using knowledge discovery and data mining. First, the paper briefly presents the background and current state-of-the-art of knowledge discovery in databases and data mining systems and projects. Next, enterprise knowledge engineering is dealt with. The paper suggests a novel approach of utilizing existing enterprise reference architectures, integration and modeling frameworks by the introduction of new enterprise views such as mining and knowledge views. An extension and a generic exploration of the information view that already exists within some enterprise models, are also proposed. The Zachman Framework for Enterprise Architecture is also outlined against the existing architectures and the proposed enterprise framework. The main contribution of this paper is the identification and definition of a common knowledge enterprise model which represents an original combination between the previous projects on enterprise architectures and the Object Management Group (OMG) models and standards. The identified common knowledge enterprise model has therefore been designed using the OMG's Model-Driven Architecture (MDA) and Common Warehouse MetaModel (CWM), and it also follows the RM-ODP (ISO/OSI). It has been partially implemented in Java TM , Enterprise JavaBeans (EJB) and Corba/IDL. Finally, the advantages and limitations of the proposed enterprise model are outlined. IntroductionOne of the foremost challenges facing manufacturing industry nowadays is the largescale integration of their enterprise systems, along with their associated models, data, information, knowledge and web descriptions. To achieve a high level of integration of managerial and technical elements, companies are resorting to standard reference architectures and common enterprise models usually developed within international projects. On the other hand the enterprise systems generate large amounts of data which are a valuable asset and potentially an important source of new information and knowledge for improving the business of the enterprise, gaining competitive advantage in fierce markets and coping with changes and managerial complexity. Large organizations such as manufacturing companies could respond to changes and challenges in their business and production activities by using intensive and intelligent database processing to identify new trends and to predict and improve their business performance. Therefore knowledge discovery (KD) in databases is a promising solution and this paper is focused on using emerging knowledge technologies such as data mining for enterprise integration and modeling. However, a comprehensive and comparative review of literature related to knowledge discovery, data mining and enterprise integration and modeling approaches reveals that there is not any reported interdisciplinary research. This paper suggests that extending the existing enterprise modeling and integration architectures and environments to inco...

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