Failure Mode & Effect Analysis for Improving Data Veracity and Validity

Abstract

Failure Mode & Effect Analysis (FMEA) is a method that has been used to improve reliability of products, processes, designs, and software for different applications, including electronics manufacturing. In this paper we propose a modification of this method to extend its application for data veracity and validity improvement. The proposed DVV-FMEA method is based on engineering features and in addition, provides transparency and understandability of the data and its pre-processing, making it reproducible and trustful.

Methods for Assessing, Predicting, and Improving Data Veracity: A survey

“…In addition, different metrics were identified to represent the veracity of web data. Some have related data veracity to the confidence level (i.e., integrity, availability, completeness, consistency, and accuracy) of the data and its sources (Berti-Équille, 2015;Herrera et al, 2019;Patgiri and Ahmed, 2016;Moyne and Iskandar, 2017;Batista et al, 2017). Debattista measured veracity in terms of dereferenceability and consistency (Debattista et al, 2015).…”

“…Failure mode and effect analysis (FMEA) is a different approach that was proposed to improve both the veracity and validity of the data (DVV-FMEA) (Herrera et al, 2019). It lists the system components and the relationships between them as well as the failure modes and the reason for each failure.…”