Data Quality Management Framework for Smart Grid Systems

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F19%3A00109300" target="_blank" >RIV/00216224:14330/19:00109300 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-030-20482-2_24" target="_blank" >http://dx.doi.org/10.1007/978-3-030-20482-2_24</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-20482-2_24" target="_blank" >10.1007/978-3-030-20482-2_24</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Data Quality Management Framework for Smart Grid Systems

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Data Quality Management Framework for Smart Grid Systems

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/EF16_019%2F0000822" target="_blank" >EF16_019/0000822: Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 22nd International Conference on Business Information Systems

ISBN

9783030204815

ISSN

1865-1348

e-ISSN

1865-1356

Počet stran výsledku

12

Strana od-do

299-310

Název nakladatele

Springer

Místo vydání

Switzerland

Místo konání akce

Switzerland

Datum konání akce

1. 1. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000490868400024