國立虎尾科技大學 |

Data Quality Management with Semantic Technologies

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Data Quality Management with Semantic Technologies/ by Christian Fürber.
作者:	Fürber, Christian.
面頁冊數:	XXVII, 205 p. 63 illus.online resource. :
Contained By:	Springer Nature eBook
標題:	Management information systems. -
電子資源:	https://doi.org/10.1007/978-3-658-12225-6
ISBN:	9783658122256

Data Quality Management with Semantic Technologies
Fürber, Christian.

Data Quality Management with Semantic Technologies[electronic resource] /by Christian Fürber. - 1st ed. 2016. - XXVII, 205 p. 63 illus.online resource.

Christian Fürber investigates the useful application of semantic technologies for the area of data quality management. Based on a literature analysis of typical data quality problems and typical activities of data quality management processes, he develops the Semantic Data Quality Management framework as the major contribution of this thesis. The SDQM framework consists of three components that are evaluated in two different use cases. Moreover, this thesis compares the framework to conventional data quality software. Besides the framework, this thesis delivers important theoretical findings, namely a comprehensive typology of data quality problems, ten generic data requirement types, a requirement-centric data quality management process, and an analysis of related work. Contents Data Quality and Semantic Technology Basics Data Quality in the Semantic Web Architecture and Evaluation of the Semantic Data Quality Management Framework Target Groups Researchers and students in the fields of economics, information systems and computer science Practitioners in the areas of data management, process management and business intelligence The Author Dr. Christian Fürber completed his doctoral study under the supervision of Prof. Dr. Martin Hepp at the E-Business and Web Science Research Group of the Universität der Bundeswehr München. He is founder and CEO of the Information Quality Institute GmbH, a company that consults organizations of any size to improve the quality of their data.

ISBN: 9783658122256

Standard No.: 10.1007/978-3-658-12225-6doiSubjects--Topical Terms:

561123
Management information systems.

LC Class. No.: HD30.2

Dewey Class. No.: 658.4038

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