IoT Data Quality Issues and Potential Solutions: A Literature Review

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14560%2F23%3A00129953" target="_blank" >RIV/00216224:14560/23:00129953 - isvavai.cz</a>
Result on the web
<a href="https://academic.oup.com/comjnl/advance-article-abstract/doi/10.1093/comjnl/bxac014/6529197?redirectedFrom=fulltext" target="_blank" >https://academic.oup.com/comjnl/advance-article-abstract/doi/10.1093/comjnl/bxac014/6529197?redirectedFrom=fulltext</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1093/comjnl/bxab183" target="_blank" >10.1093/comjnl/bxab183</a>

Result language
angličtina
Original language name
IoT Data Quality Issues and Potential Solutions: A Literature Review
Original language description
In the Internet of Things (IoT), data gathered from dozens of devices are the base for creating business value and developing new products and services. If data are of poor quality, decisions are likely to be non-sense. Data quality is crucial to gain business value of the IoT initiatives. This paper presents a systematic literature review regarding IoT data quality from 2000 to 2020. We analyzed 58 articles to identify IoT data quality dimensions and issues and their categorizations. According to this analysis, we offer a classification of IoT data characterizations using the focus group method and clarify the link between dimensions and issues in each category. Manifesting a link between dimensions and issues in each category is incumbent, while this critical affair in extant categorizations is ignored. We also examine data security as an important data quality issue and suggest potential solutions to overcome IoT's security issues. The finding of this study proposes a new research discipline for additional examination for researchers and practitioners in determining data quality in the context of IoT.
Czech name
—
Czech description
—

Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
50204 - Business and management

Project
<a href="/en/project/EF16_027%2F0008360" target="_blank" >EF16_027/0008360: Postdoc@MUNI</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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