國立高雄大學圖資館 |

Language: English

Back

Data quality management with semanti...

Furber, Christian.

Data quality management with semantic technologies

Record Type:	Electronic resources : Monograph/item
Title/Author:	Data quality management with semantic technologiesby Christian Furber.
Author:	Furber, Christian.
Published:	Wiesbaden :Springer Fachmedien Wiesbaden :2016.
Description:	xxvii, 205 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Database management.
Online resource:	http://dx.doi.org/10.1007/978-3-658-12225-6
ISBN:	9783658122256$q(electronic bk.)

Data quality management with semantic technologies
Furber, Christian.

Data quality management with semantic technologies[electronic resource] /by Christian Furber. - Wiesbaden :Springer Fachmedien Wiesbaden :2016. - xxvii, 205 p. :ill., digital ;24 cm.

Christian Furber 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 Furber completed his doctoral study under the supervision of Prof. Dr. Martin Hepp at the E-Business and Web Science Research Group of the Universitat der Bundeswehr Munchen. 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$q(electronic bk.)

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

182428
Database management.

LC Class. No.: QA76.9.D3 / F73 2016

Dewey Class. No.: 005.7565

Data quality management with semantic technologies
LDR:02433nmm a2200301 a 4500 001 482194
003 DE-He213
005 20160805142835.0
006 m d
007 cr nn 008maaau
008 161007s2016 gw s 0 eng d
020 $a 9783658122256$q(electronic bk.)
020 $a 9783658122249$q(paper)
024 7 $a 10.1007/978-3-658-12225-6 $2 doi
035 $a 978-3-658-12225-6
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.D3 $b F73 2016
072 7 $a KJQ $2 bicssc
072 7 $a COM005030 $2 bisacsh
082 0 4 $a 005.7565 $2 23
090 $a QA76.9.D3 $b F983 2016
100 1 $a Furber, Christian. $3 738757
245 1 0 $a Data quality management with semantic technologies $h [electronic resource] / $c by Christian Furber.
260 $a Wiesbaden : $b Springer Fachmedien Wiesbaden : $b Imprint: Springer Gabler, $c 2016.
300 $a xxvii, 205 p. : $b ill., digital ; $c 24 cm.
520 $a Christian Furber 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 Furber completed his doctoral study under the supervision of Prof. Dr. Martin Hepp at the E-Business and Web Science Research Group of the Universitat der Bundeswehr Munchen. 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.
650 0 $a Database management. $3 182428
650 0 $a Databases $x Quality control. $3 208206
650 0 $a Semantic Web. $3 208252
650 1 4 $a Business and Management. $2 eflch $3 639169
650 2 4 $a Business Information Systems. $3 274346
650 2 4 $a Knowledge Management. $3 277143
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
856 4 0 $u http://dx.doi.org/10.1007/978-3-658-12225-6
950 $a Business and Management (Springer-41169)