DQA4AirQuality: TDQM-Based Data Quality Assessment Framework for Air Quality Datasets


Lina Zhang, Sukhoon Lee, Journal of Information Processing Systems Vol. 21, No. 1, pp. 13-27, Mar. 2025  

https://doi.org/10.3745/JIPS.04.0332
Keywords: Air Quality, Big data, Data Quality Assessment, Open Data
Fulltext:

Abstract

In recent years, open government data and big data analytic applications have become increasingly widespread. Without proper quality control, the rapid dissemination of data may jeopardize the reuse of datasets and exert negative effects. The current general frameworks for data quality management in literature are outdated and lack extensions to big and open data. In this work, a four-level data quality assessment dimension generation model was developed and applied for air quality datasets to measure the quality of air quality data from various data quality dimensions. This assessment framework was validated by comparing it with four air quality datasets from the World Health Organization (WHO), Beijing, Seoul, and Italy. The results show that the datasets published by the WHO have low quality due to their more complex sources.


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Cite this article
[APA Style]
Zhang, L. & Lee, S. (2025). DQA4AirQuality: TDQM-Based Data Quality Assessment Framework for Air Quality Datasets. Journal of Information Processing Systems, 21(1), 13-27. DOI: 10.3745/JIPS.04.0332.

[IEEE Style]
L. Zhang and S. Lee, "DQA4AirQuality: TDQM-Based Data Quality Assessment Framework for Air Quality Datasets," Journal of Information Processing Systems, vol. 21, no. 1, pp. 13-27, 2025. DOI: 10.3745/JIPS.04.0332.

[ACM Style]
Lina Zhang and Sukhoon Lee. 2025. DQA4AirQuality: TDQM-Based Data Quality Assessment Framework for Air Quality Datasets. Journal of Information Processing Systems, 21, 1, (2025), 13-27. DOI: 10.3745/JIPS.04.0332.