Data validation and data quality assessment

Francois Clemens*, Mathieu Lepot, Frank Blumensaat, Dominik Leutnant, Guenter GRUBER

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


Once data have been recorded, data validation procedures have to be conducted to assess the quality of the data, i.e. give a confidence grade. Furthermore, gaps may occur in time series and, depending on the purposes, these can be given values by application of e.g. interpolation. Since both aspects are strongly
correlated, this chapter gives an overview on the main data validation and data curation/imputation methods. Instead of offering exhaustive details on existing methods, this chapter aims at providing concepts for most popular techniques, a discussion of their advantages and disadvantages in the light of different cases of application, and some thoughts on potential impacts of the choices that must be made. Despite involving mathematical methods, data validation remains a largely subjective process: every data user must be aware of those subjectivities.
Original languageEnglish
Title of host publicationMetrology in Urban Drainage and Stormwater Management: Plug and Pray
PublisherIWA Publishing
ChapterChapter 9
Pages327 - 390
Number of pages64
ISBN (Electronic)9781789060119
Publication statusPublished - Aug 2021


  • metrology, urban drainage, stormwater management, data validation, data quality assessment

Fields of Expertise

  • Sustainable Systems

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