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Quality Measures for Semantic Web Application

Quality Measures for Semantic Web Application

Adiraju Prasanth Rao
Copyright: © 2016 |Pages: 10
ISBN13: 9781466697645|ISBN10: 1466697644|EISBN13: 9781466697652
DOI: 10.4018/978-1-4666-9764-5.ch005
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MLA

Rao, Adiraju Prasanth. "Quality Measures for Semantic Web Application." Design Solutions for Improving Website Quality and Effectiveness, edited by G. Sreedhar, IGI Global, 2016, pp. 130-139. https://doi.org/10.4018/978-1-4666-9764-5.ch005

APA

Rao, A. P. (2016). Quality Measures for Semantic Web Application. In G. Sreedhar (Ed.), Design Solutions for Improving Website Quality and Effectiveness (pp. 130-139). IGI Global. https://doi.org/10.4018/978-1-4666-9764-5.ch005

Chicago

Rao, Adiraju Prasanth. "Quality Measures for Semantic Web Application." In Design Solutions for Improving Website Quality and Effectiveness, edited by G. Sreedhar, 130-139. Hershey, PA: IGI Global, 2016. https://doi.org/10.4018/978-1-4666-9764-5.ch005

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Abstract

The Semantic Web is a standard of Common Data Formats on WWW with aim to convert the current web data of unstructured and semi-structured documents into a common framework that allows data to be shared and reused across applications, enterprises. The main purpose of the Semantic Web is driving the evolution of the current Web by enabling users to find, share, and combine information more easily. Humans are capable of using the Web to carry out tasks such as searching for the lowest price for a LAPTOP. However, machines cannot accomplish all of these tasks without human direction, because web pages are designed to be read by people, not machines. The semantic web is a vision of information that can be readily interpreted by machines, so machines can perform more of the tedious work involved in finding, combining, and acting upon information on the web. The chapter presents the architecture of semantic web, its challenging issues and also data quality principles. These principles provide a better decision making within organization and will maximize long term data integration and interoperability.

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