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International audience; This paper presents study of 115 grounding accident reports from the Safety Investigation Authority of Finland and Marine Accident Investigation Branch of the UK, as well as 163 near-miss grounding reports from ForeSea and Finnpilot incident databases. The objective was to find the type of knowledge that can be extracted from such sources and discuss the usability of accident and incident reports for evidence-based risk modeling. A new version of Human Factors Analysis and Classification System (HFACS) is introduced as a framework to review the accident reports. The new positive taxonomy as Safety Factors, which are based on high level positive functions that are prerequisite for safe transport operations, is used for reviewing the incident reports. Accident reports are shown as a reliable source of evidence to extract the most significant contributing factors in the events. Mandatory incident reports are considered useful for understanding the effective barriers as risk control measures. Voluntary incident reports, though, are seen as not very reliable in their current form to be used for evidence-based risk modeling.

Modern Flight Operations Monitoring tools have satisfied the hunger for safety data on minor events and deviations - and thus set the scene for very proactive safety management. There remains, however, the conceptual challenge of how to learn effectively from such data. While the initial case-by-case analysis is usually straightforward, the classical keyword-based analysis methods only give limited support to a more proactive trending type of analysis on the whole database of events. The paper suggests that new methods based on top-down safety models are a very promising option in facing the challenge. The promises and main uncertainties of such methods are discussed. The paper also argues that the term “risk management” is often used lightly in the context of safety processes, which are far from rigorous and systematic risk assessment and management.