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Communication Dans Un Congrès Année : 2022

5D-IoT, a semantic web based framework for assessing IoT data quality

Résumé

Due to the increasing number of Internet of Things (IoT) devices, a large amount of data is being generated. However, factors such as hardware malfunctions, network failures, or cyber-attacks affect data quality and result in inaccurate data generation. Therefore, to facilitate the data usage, we propose a novel 5D-IoT framework for heterogeneous IoT systems that provides uniform data quality assessment with meaningful data descriptions. Based on the quality assessment result, a data consumer can directly access data from any IoT source, which ultimately speeds up the analysis process and helps gain important insights in less time. The framework relies on semantic descriptions of sensor observations and SHACL shapes assessing the quality of such data. Evaluations carried out on real-time data show the added value of such a framework.
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Dates et versions

hal-04279670 , version 1 (10-11-2023)

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Nathalie Jane Hernandez, Shubham Mante, Aftab M Hussain, Sachin Chaudhari, Deepak Gangadharan, et al.. 5D-IoT, a semantic web based framework for assessing IoT data quality. 37th ACM/SIGAPP Symposium on Applied Computing (SAC 2022), Apr 2022, Virtual Event, France. pp.1921-1924, ⟨10.1145/3477314.3507234⟩. ⟨hal-04279670⟩
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