DATA QUALITY IN IOT OPEN DATASETS A METHODOLOGICAL REVIEW
Abstract
The growth of the Internet of Things (IoT) has significantly increased data generated by connected devices, leading to challenges in data duplication that threaten data quality and reliability. The purpose of this study is to assess and thoroughly examine the quality of open-source IoT datasets, focusing on the occurrence and impact of duplicate data. By employing a Systematic Literature Review (SLR) and a literature-based comparative analysis, we reviewed and compared existing techniques for detecting these issues. Our findings reveal that while various methods have been proposed, there remains a lack of standardized approaches specifically designed for the unique characteristics of IoT environments. The study concludes by highlighting the need for more reliable and scalable solutions that are capable of handling the diverse and dynamic nature of IoT data, also offering insights into future research directions.
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