Podrobný výpis o publikaci

HELFERT, Markus a Mouzhi GE. Perspectives of Big Data Quality in Smart Service Ecosystem. Journal of Information Technology Management. 2018, roč. 10, č. 4, s. 72-83. ISSN 2008-5893. Dostupné z: https://dx.doi.org/10.22059/JITM.2019.72763.

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Základní údaje
Originální název	Perspectives of Big Data Quality in Smart Service Ecosystem
Autoři	HELFERT, Markus (276 Německo) a Mouzhi GE (156 Čína, garant, domácí).
Vydání	Journal of Information Technology Management, 2018, 2008-5893.

Další údaje
Originální jazyk	angličtina
Typ výsledku	Článek v odborném periodiku
Obor	10201 Computer sciences, information science, bioinformatics
Stát vydavatele	Írán
Utajení	není předmětem státního či obchodního tajemství
WWW	URL
Kód RIV	RIV/00216224:14330/18:00111068
Organizační jednotka	Fakulta informatiky
Doi	http://dx.doi.org/10.22059/JITM.2019.72763
Klíčová slova anglicky	Big data quality; Information quality; Smart cities; Service design; Smart services; Data quality model; Smart service ecosystem
Příznaky	Mezinárodní význam, Recenzováno
Změnil	Změnil: RNDr. Pavel Šmerk, Ph.D., učo 3880. Změněno: 6. 5. 2020 11:15.

Anotace
Despite the increasing importance of data and information quality, current research related to Big Data quality is still limited. It is particularly unknown how to apply previous data quality models to Big Data. In this paper we review Big Data quality research from several perspectives and apply a known quality model with its elements of conformance to specification and design in the context of Big Data. Furthermore, we extend this model and demonstrate it utility by analyzing the impact of three Big Data characteristics such as volume, velocity and variety in the context of smart cities. This paper intends to build a foundation for further empirical research to understand Big Data quality and its implications in the design and execution of smart service ecosystems.

Anotace

Despite the increasing importance of data and information quality, current research related to Big Data quality is still limited. It is particularly unknown how to apply previous data quality models to Big Data. In this paper we review Big Data quality research from several perspectives and apply a known quality model with its elements of conformance to specification and design in the context of Big Data. Furthermore, we extend this model and demonstrate it utility by analyzing the impact of three Big Data characteristics such as volume, velocity and variety in the context of smart cities. This paper intends to build a foundation for further empirical research to understand Big Data quality and its implications in the design and execution of smart service ecosystems.