Data Quality Management Framework for Smart Grid Systems

D 2019

Data Quality Management Framework for Smart Grid Systems

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

Základní údaje

Originální název

Data Quality Management Framework for Smart Grid Systems

Autoři

GE, Mouzhi (156 Čína, garant, domácí), Stanislav CHREN (703 Slovensko, domácí), Bruno ROSSI (380 Itálie, domácí) a Tomáš PITNER (203 Česká republika, domácí)

Vydání

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

Nakladatel

Springer

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Německo

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

elektronická verze "online"

Kód RIV

RIV/00216224:14330/19:00109300

Organizační jednotka

Fakulta informatiky

ISBN

978-3-030-20481-5

ISSN

DOI

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

UT WoS

000490868400024

Klíčová slova anglicky

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

Štítky

core_B, firank_B

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 3. 5. 2020 11:14, RNDr. Pavel Šmerk, Ph.D.

Anotace

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.

Návaznosti

EF16_019/0000822, projekt VaV

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

Citovat

GE, Mouzhi, Stanislav CHREN, Bruno ROSSI a 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, s. 299-310. ISBN 978-3-030-20481-5. Dostupné z: 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 a 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, s.~299-310. ISBN~978-3-030-20481-5. Dostupné z: https://dx.doi.org/10.1007/978-3-030-20482-2\_{}24.

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