@inproceedings{da3e2957bcd348c49c444f675257c364,
title = "A competency question driven approach to conceptual data model design for digital verification and validation",
abstract = "This work introduces a data-driven credibility assessment to quantify simulation quality in industrial part re-manufacturing. The framework evaluates the dependability of sources, data, and methodologies, focusing on robustness and uncertainty for data quality and simulation confidence. A conceptual data model, designed using competency questions, maps data requirements, digitalising credibility evaluation and promoting data traceability and accessibility.",
keywords = "data quality, credibility assessment, simulation quality, data traceability, conceptual data model",
author = "Joao Gregorio and Moulham Alsuleman and Michael Chrubasik and Paul Duncan and Graeme Bisland",
year = "2024",
month = dec,
day = "31",
doi = "10.1142/9789819800674\_0006",
language = "English",
isbn = "9789819800667",
series = "Series on Advances in Mathematics for Applied Sciences",
publisher = "World Scientific",
pages = "71--82",
editor = "F. Pavese and A. Bo{\v s}njakovi{\'c} and S. Eichst{\"a}dt and A.B. Forbes and J.A. Sousa",
booktitle = "Advanced Mathematical and Computational Tools in Metrology and Testing XIII",
address = "Singapore",
}