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Spotlight September: A methodology for the automatic evaluation of data quality and completeness of nanomaterials for risk assessment purposes
This paper describes a method for automatically assessing the quality and completeness of nanosafety data for the purpose of risk assessment. Steps to develop the methodology for assessing data completeness and the methodology for assessing quality are presented. The methodology is tailored to physicochemical and hazard (meta) data, but can also be configured with appropriate criteria to support modeling or exposure assessment. It is based on assessing the quality and completeness of the data contained in the eNanoMapper database using the harmonized data reporting templates introduced in the NANoREG project and further developed in the GRACIOUS project. Combined with expert knowledge, this methodology can be used as a powerful data analysis tool in different contexts. To enable the practical application of the proposed methodology, it has been implemented as an online R-tool (https://shinyapps.greendecision.eu/app/gracious-data-quality) that can be connected to both databases and risk assessment software tools.
Original publication:
Gianpietro Basei, Hubert Rauscher, Nina Jeliazkova & Danail Hristozov (2022). A methodology for the automatic evaluation of data quality and completeness of nanomaterials for risk assessment purposes. Nanotoxicology, 16:2, 195-216, DOI: 10.1080/17435390.2022.2065222
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