Abstract
Nowadays, IoT is being used in more and more application areas and the importance of IoT data quality is widely recognized by practitioners and researchers. The requirements for data and its quality vary from application to application or organization in different contexts. Many methodologies and frameworks include techniques for defining, assessing, and improving data quality. However, due to the diversity of requirements, it can be a challenge to choose the appropriate technique for the IoT system. This paper surveys data quality frameworks and methodologies for IoT data, and related international standards, comparing them in terms of data types, data quality definitions, dimensions and metrics, and the choice of assessment dimensions. The survey is intended to help narrow down the possible choices of IoT data quality management technique.
Funder
National Research Foundation of Korea
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry
Reference95 articles.
1. That ‘internet of things’ thing;Ashton;RFID J.,2009
2. Internet of Things: Objectives and Scientific Challenges
3. Global Number of Publicly Known IoT Platforms 2015–2019https://www.statista.com/statistics/1101483/global-number-iot-platform/
4. Data Volume of IoT Connected Devices Worldwide 2019 and 2025https://www.statista.com/statistics/1017863/worldwide-iot-connected-devices-data-size/
5. Sensor data quality: a systematic review
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