Abstract
A Knowledge Management (KM) System plays a crucial role in every industry as well as in Higher Learning Institutions. A RESTful resource is anything that is addressable over the Web. The resources can be accessed and transferred between clients and server. The resources can be accessed and transferred between clients and servers. Based on our earlier research works, we have developed a comprehensive KM System framework, evaluation method, mult-dimensional metric model and useful metrics which are helpful to assess any given knowledge management system. In this proposed work, we first describe the actual implementation steps for building the KM System metric database using the multi-dimensional metric model. Secondly we describe the approaches for designing a multi-dimensional Restful Resources and Web Services using the mutli-dimensional metric model and demonstrate how the KM system can be ranked and rated for its effectiveness using WAM and RESTful Resources.
Highlights
Knowledge Management (KM) provides an innovative methodology for creating and modifying to promote knowledge creation and sharing
The selected measures which are generated manually or through system way should be stored in any available database and later those will be retrieved for ranking and rating using Weighted Average Mean Method
Continuous Inputs for the Knowledge Management Systems (KMS) Measurement process can be done through standard system programs or tools to monitor the usefulness and responsiveness of supporting technology or the framework or components used for the KMS
Summary
Knowledge Management (KM) provides an innovative methodology for creating and modifying to promote knowledge creation and sharing. Many companies and institutions are working towards building an effective KMS as well as using collaborative tools for increasing the knowledge sharing with their knowledge workers. One of the key challenges with the KMS’s is evaluation of the knowledge available within the organization and assessing the capabilities and effectiveness of the KMS infrastructure [1]. Considering the intangible nature of the knowledge asset, complexity and dynamics of building the KM System infrastructure, one of an approach is, to determine the strengths and weakness through metrics. Based on many research works, it has been identified that there are no proven reliable metric model and metric database to estimate and report the worth of the knowledge being shared and the worth of KM Systems.
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