Perspectives of Big Data Quality in Smart Service Ecosystem

HELFERT, Markus and Mouzhi GE. Perspectives of Big Data Quality in Smart Service Ecosystem. Journal of Information Technology Management. 2018, vol. 10, No 4, p. 72-83. ISSN 2008-5893. Available from: https://dx.doi.org/10.22059/JITM.2019.72763.

Basic information

• Original name: Perspectives of Big Data Quality in Smart Service Ecosystem
• Authors: HELFERT, Markus (276 Germany) and Mouzhi GE (156 China, guarantor, belonging to the institution).
• Edition: Journal of Information Technology Management, 2018, 2008-5893.

Other information

• Original language: English
• Type of outcome: Article in a journal
• Field of Study: 10201 Computer sciences, information science, bioinformatics
• Country of publisher: Islamic Republic of Iran
• Confidentiality degree: is not subject to a state or trade secret
• WWW: URL
• RIV identification code: RIV/00216224:14330/18:00111068
• Organization unit: Faculty of Informatics
• Doi: http://dx.doi.org/10.22059/JITM.2019.72763
• Keywords in English: Big data quality; Information quality; Smart cities; Service design; Smart services; Data quality model; Smart service ecosystem
• Tags: International impact, Reviewed

Abstract

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.