Readiness of the taxonomy used by ECCAIRS 2 for Causal Analysis based on Systems Theory

Abstract

This paper examines whether the taxonomy used by the European Co-ordination Centre for Accident and Incident Reporting Systems (ECCAIRS 2) can provide suitable inputs for Causal Analysis based on Systems Theory (CAST), a method grounded in the System-Theoretic Accident Model and Processes (STAMP). The methodology combines analysis of CAST inputs and outputs with Semantic Web technologies, Unified Modeling Language (UML) and Business Process Model and Notation (BPMN) diagrams to map ECCAIRS 2 entities, attributes, and values to individual CAST steps. A representation of the ECCAIRS 2 taxonomy and an ontology implemented in Protégé were developed to support querying and traceability, and the approach was validated using four real aviation occurrences recorded in ECCAIRS 2 for which CAST analyses were available. The results show that key ECCAIRS 2 attributes can systematically support CAST activities such as defining system boundaries, identifying losses and system-level hazards, identifying controllers of the safety control structure, and formulating Unsafe Control Actions and systemic causal factors. The findings confirm that the ECCAIRS 2 taxonomy can be used as a structured input source for CAST, while highlighting limitations related to incomplete coverage of CAST activities, constrained representation of system context and interactions, and dependence on the quality of occurrence reports. The proposed methodology offers a decision-support framework that enhances consistency, transparency, and efficiency of STAMP-based accident and incident investigations and provides a basis for further tool development and partial automation.

The authors' abstract, as published at the source. Safety Science, 2026 · DOI ↗