| The software deployment process is inherently complex involving multiple components and collaboration between organizations. It is a knowledge intensive process that requires dynamic access to diverse data, information, and knowledge to support both technical and business requirements. This research introduces the Ontology-based Knowledge Discovery and Management System (OKDMS), to improve the software deployment process by examining the problems of data inconsistencies, identification, discovery, representation of software deployment resources and business requirements. The OKDMS is based on an integration enablement paradigm of the software deployment process with knowledge management of the diverse data elements to make the deployment process dynamic and less complex. The proposed approach of OKDMS enables the discovery, integration, sharing, and reuse of data and information related to the business requirements and focuses on creating knowledge by understanding the deployment process in its entirety. The essential contribution is that the proposed OKDMS improves the accuracy, consistency, quality, and productivity of the software deployment process by automating multi deployment scheduling, discovery, and mapping of concurrent data and information. It also provides a mechanism for searching, indexing, and centralizing information, and aims to standardize document sharing and common understanding of software deployment concepts. The pilot testing of the OKDMS in a real world environment proved that the rate of software deployments increased by a factor of 58% while reducing installation errors by 57% over a period of one month. |
