Data Quality Assessment: A Practical  Application

Eliana Costa e Silva; Teresa Peixoto; Óscar Oliveira; Bruno Oliveira

http://hdl.handle.net/10400.22/30219

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Abstract(s)

This paper presents a novel data quality score designed to address the challenges of ensuring high-quality data in Internet of Things (IoT) deployments. Given the growing reliance on IoT systems and the volume of data they generate, maintaining data quality is essential for reliable decision-making and eﬀective analytics. The proposed score synthesizes key data quality dimensions, providing a comprehensive measure of data quality that can be applied across various IoT contexts. The results obtained for a public dataset on a water pumping system show the applicability and ﬂexibility of the proposed data quality score. This work contributes to the ongoing eﬀorts to improve data management in IoT environments, ultimately supporting the development of robust, data-driven solutions.