5D-IoT, a semantic web based framework for assessing IoT data quality
Open accessAbstract
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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IoT Data Quality Assessment Framework Using Adaptive Weighted Estimation Fusion
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Bamgboye, O., Liu, X., Cruickshank, P., & Liu, Q. (2025) · Big Data and Cognitive Computing · doi:10.3390/bdcc9040108 · Cited by 4 · see citing works
“A more recent approach [14] focused on applying the semantic framework for enriching the IoT data and using this with SHACL to perform IoT data quality assessment.”
- Authors
- Mante, S., Hernandez, N., Hussain, A. M., Chaudhari, S., Gangadharan, D., & Monteil, T.
- Affiliations
- International Institute of Information Technology, Hyderabad (IN)
- University of Toulouse, Toulouse, France
- Venue
- Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing
- Publisher
- ACM
- Published
- 2022-04-25
- Pages
- 1921-1924
- OpenAlex
- W4229018183
- Cited by
- 5
- References
- 9
- Citations by year
- 2025: 3 · 2023: 2
- FWCI
- 0.69
- Type
- conference paper
- Language
- en
- Open access
- green
- hal.science
- Locations
- ACM Symposium on Applied Computing (publishedVersion)
- HAL (submittedVersion, other-oa)
- Funders
- Ministry of Electronics and Information Technology (MEITY) , INDIA (3070665 (2020))
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Semantic Web and Ontologies
- Social Sciences › Decision Sciences › Management Science and Operations Research › Data Quality and Management
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Keywords
- Internet of Things, data quality assessment, semantic web, SHACL, sensor observations, data description, data integration
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