Data Quality Management Framework for Smart Grid Systems

D 2019

Data Quality Management Framework for Smart Grid Systems

GE, Mouzhi, Stanislav CHREN, Bruno ROSSI and Tomáš PITNER

Basic information

Original name

Data Quality Management Framework for Smart Grid Systems

Authors

GE, Mouzhi (156 China, guarantor, belonging to the institution), Stanislav CHREN (703 Slovakia, belonging to the institution), Bruno ROSSI (380 Italy, belonging to the institution) and Tomáš PITNER (203 Czech Republic, belonging to the institution)

Edition

Switzerland, Proceedings of the 22nd International Conference on Business Information Systems, p. 299-310, 12 pp. 2019

Publisher

Springer

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Germany

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

electronic version available online

RIV identification code

RIV/00216224:14330/19:00109300

Organization unit

Faculty of Informatics

ISBN

978-3-030-20481-5

ISSN

DOI

http://dx.doi.org/10.1007/978-3-030-20482-2_24

UT WoS

000490868400024

Keywords in English

Smart grid; Data quality; Data quality problem; Smart meter

Abstract

V originále

New devices in smart grid such as smart meters and sensors have emerged to become a massive and complex network, where a large volume of data is flowing to the smart grid systems. Those data can be real-time, fast-moving, and originated from a vast variety of terminal devices. However, the big smart grid data also bring various data quality problems, which may cause the delayed, inaccurate analysis of results, even fatal errors in the smart grid system. This paper, therefore, identifies a comprehensive taxonomy of typical data quality problems in the smart grid. Based on the adaptation of established data quality research and frameworks, this paper proposes a new data quality management framework that classifies the typical data quality problems into related data quality dimensions, contexts, as well as countermeasures. Based on this framework, this paper not only provides a systematic overview of data quality in the smart grid domain, but also offers practical guidance to improve data quality in smart grids such as which data quality dimensions are critical and which data quality problems can be addressed in which context.

Links

EF16_019/0000822, research and development project

Name: Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur

Citovat

GE, Mouzhi, Stanislav CHREN, Bruno ROSSI and Tomáš PITNER. Data Quality Management Framework for Smart Grid Systems. Online. In Abramowicz W., Corchuelo R. Proceedings of the 22nd International Conference on Business Information Systems. Switzerland: Springer, 2019, p. 299-310. ISBN 978-3-030-20481-5. Available from: https://dx.doi.org/10.1007/978-3-030-20482-2_24.

@inproceedings{1506236,
   author = {Ge, Mouzhi and Chren, Stanislav and Rossi, Bruno and Pitner, Tomáš},
   address = {Switzerland},
   booktitle = {Proceedings of the 22nd International Conference on Business Information Systems},
   doi = {http://dx.doi.org/10.1007/978-3-030-20482-2_24},
   editor = {Abramowicz W., Corchuelo R.},
   keywords = {Smart grid; Data quality; Data quality problem; Smart meter},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {Switzerland},
   isbn = {978-3-030-20481-5},
   pages = {299-310},
   publisher = {Springer},
   title = {Data Quality Management Framework for Smart Grid Systems},
   year = {2019}
}

TY  - JOUR
ID  - 1506236
AU  - Ge, Mouzhi - Chren, Stanislav - Rossi, Bruno - Pitner, Tomáš
PY  - 2019
TI  - Data Quality Management Framework for Smart Grid Systems
PB  - Springer
CY  - Switzerland
SN  - 9783030204815
KW  - Smart grid
KW  - Data quality
KW  - Data quality problem
KW  - Smart meter
N2  - New devices in smart grid such as smart meters and sensors have emerged to become a massive and complex network, where a large volume of data is flowing to the smart grid systems. Those data can be real-time, fast-moving, and originated from a vast variety of terminal devices. However, the big smart grid data also bring various data quality problems, which may cause the delayed, inaccurate analysis of results, even fatal errors in the smart grid system. This paper, therefore, identifies a comprehensive taxonomy of typical data quality problems in the smart grid. Based on the adaptation of established data quality research and frameworks, this paper proposes a new data quality management framework that classifies the typical data quality problems into related data quality dimensions, contexts, as well as countermeasures. Based on this framework, this paper not only provides a systematic overview of data quality in the smart grid domain, but also offers practical guidance to improve data quality in smart grids such as which data quality dimensions are critical and which data quality problems can be addressed in which context.
ER  -

GE, Mouzhi, Stanislav CHREN, Bruno ROSSI and Tomáš PITNER. Data Quality Management Framework for Smart Grid Systems. Online. In Abramowicz W., Corchuelo R. \textit{Proceedings of the 22nd International Conference on Business Information Systems}. Switzerland: Springer, 2019, p.~299-310. ISBN~978-3-030-20481-5. Available from: https://dx.doi.org/10.1007/978-3-030-20482-2\_{}24.

Detailed Information on Publication Record