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Degree

Master of Science in Software Engineering, Cleveland State University, Fenn College of Engineering, 2012.

Abstract

Podcasting has emerged as an asynchronous delay-tolerant method for the distribution of multimedia files through a network. Although podcasting has become a popular Internet application, users encounter frequent information quality problems in podcasting systems. To better understand the severity of these quality problems, we have applied the Total Data Quality Management methodology to podcasting. Through the application of this methodology we have quantified the data quality problems inherent within podcasting metadata, and performed an analysis that maps specific metadata defects to failures in popular commercial podcasting platforms. Furthermore, we extracted the Really Simple Syndication (RSS) feeds from the iTunes catalog for the purpose of performing the most comprehensive measurement of podcasting metadata to date. From these findings we attempted to improve the quality of podcasting data through the creation of a metadata validation tool - PodCop. PodCop extends existing RSS validation tools and encapsulates validation rules specific to the context of podcasting. We believe PodCop is the first attempt at improving the overall health of the podcasting ecosystem.

Subject Headings

Computer Science

Keywords

podcast; podcasting; data quality, TDQM

Committee / Advisors

Nigamanth Sridhar, PhD (Committee Chair)
Yongjian Fu, PhD (Committee Member)
Wenbing Zhao, PhD (Committee Member)

Pages

122p.

Document number: csu1354742093
Permalink: http://rave.ohiolink.edu/etdc/view?acc_num=csu1354742093

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