Cyclic knowledge management system in e-governance: a case study of evaluating polls on referendum-independence of quebec using ANN

Abstract

E-Governance brings urban and rural together and breaks the barrier of distance to lead an efficient administration. Surprisingly, E-Governance have not made enough impact on the people as e-Commerce and e-Learning have done. From the software engineering point of view, E-Governance has a lot of characteristics, which are different from e-Commerce and e-Learning. It is enough for e-Commerce and e-Learning to be reactive whereas E-Governance needs to be proactive. While e-Commerce and e-Learning involve Information Management, E-Governance involves Knowledge Management (KM). Knowledge management is the management of information, skill, experience, innovation, and intelligence. Our model of E-Governance based on Knowledge Management System (KMS) is built on KM cycle of Knowledge capturing, Knowledge sharing, Knowledge enhancing, and Knowledge preserving. A few popular models of E-Governance use a concept of "knowledge centers" to share knowledge. Our model shares knowledge that supports the law of knowledge dynamics. The development model of E-Governance based on Information Management System (IMS) applies a cycle-based process such as spiral or iterative process. This paper studies a development model of KMS-based E-Governance, which is path-based. This model provides an environment where the system grows with the people. To simulate the proposed KMS model, we analyzed a scenario based on the poll on Referendum question of Quebec, CA regarding independence (unilateral action or negotiation) using Artificial Neural Network.