Quality Metrics for Evaluating Data Provenance

View Sample PDF

Author(s): Syed Ahsan (University of Engineering and Technology, Pakistan)and Abad Shah (University of Engineering and Technology, Pakistan)
Copyright: 2009
Pages: 19
Source title: Designing Software-Intensive Systems: Methods and Principles
Source Author(s)/Editor(s): Pierre F. Tiako (Langston University, USA)
DOI: 10.4018/978-1-59904-699-0.ch015

Keywords: Computer Science & IT / Information Science Reference / Systems & Software Design / Systems and Software Engineering

Purchase

View Quality Metrics for Evaluating Data Provenance on the publisher's website for pricing and purchasing information.

Abstract

With the proliferation of Web, a tremendous amount of data is available to researchers and scientists in computational sciences, business organizations and general public. This has resulted in an increased importance of data intensive domains such as Bioinformatics, which are increasingly using Web-based applications and service-oriented architecture which uses the data available on the Web sources. To trust the data available on Web and the results derived from it, a Data Provenance system must be devised to ensure authenticity and credibility of Web resources. In this paper we have discussed various domains which necessitate such data provenance systems. We propose a set of tangible parameters which affect the quality of data and define quality metrics to evaluate those parameters. The chapter concludes with a section on future directions in which we identify various research problems and possible applications of data provenance.

The IRMA Community

Research IRM

Quality Metrics for Evaluating Data Provenance

Purchase

Abstract

Related Content

IRMA Sponsors