Knowledge in graphs: investigating the completeness of industrial near miss reports

•Safety meta-analysis for near miss reports based on knowledge graphs.•Report completeness is proposed as a proxy measure for safety meta-analysis.•Completeness is obtained as data-driven measure weighted by Subject Matter Experts.•The analysis on report completeness is depicted using a novel synthetic plot.•The analysis is instantiated on safety reports by selected Seveso establishments. Learning from near misses has a large potential for improving operations especially in high-risk sectors, such as Seveso industries. A comprehensive analysis of near miss reports requires processing a large volume of data from various sources, which are not standardized and seemingly disconnected from each other. A knowledge graph is here used to provide a comprehensive safety perspective to near miss data. In particular, this paper presents an analysis of a knowledge graph for near miss reports with the objective to measure systematically their completeness based on an integrated multi-criteria decision-making technique. The reports completeness fosters a meta-analysis of available data, highlighting systems’ strengths and vulnerabilities, as well as disseminating best practices for industry stakeholders.