Language:
English
繁體中文
Help
回圖書館首頁
手機版館藏查詢
Login
Back
Switch To:
Labeled
|
MARC Mode
|
ISBD
Data quality management with semanti...
~
Furber, Christian.
Linked to FindBook
Google Book
Amazon
博客來
Data quality management with semantic technologies
Record Type:
Electronic resources : Monograph/item
Title/Author:
Data quality management with semantic technologies/ by 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:
527442
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
2029718
003
DE-He213
005
20160805142835.0
006
m d
007
cr nn 008maaau
008
160908s2016 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
2180918
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
527442
650
0
$a
Databases
$x
Quality control.
$3
873663
650
0
$a
Semantic Web.
$3
572918
650
1 4
$a
Business and Management.
$2
eflch
$3
1485455
650
2 4
$a
Business Information Systems.
$3
892640
650
2 4
$a
Knowledge Management.
$3
900242
710
2
$a
SpringerLink (Online service)
$3
836513
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)
based on 0 review(s)
Location:
ALL
電子資源
Year:
Volume Number:
Items
1 records • Pages 1 •
1
Inventory Number
Location Name
Item Class
Material type
Call number
Usage Class
Loan Status
No. of reservations
Opac note
Attachments
W9276982
電子資源
11.線上閱覽_V
電子書
EB QA76.9.D3 F983 2016
一般使用(Normal)
On shelf
0
1 records • Pages 1 •
1
Multimedia
Reviews
Add a review
and share your thoughts with other readers
Export
pickup library
Processing
...
Change password
Login