Abstract
Recent tragic marine incidents indicate that more efficient safety procedures and emergency management systems are needed. During the 2014–2019 period, 320 accidents cost 496 lives, and 5424 accidents caused 6210 injuries. Ideally, we need historical data from real accident cases of ships to develop data-driven solutions. According to the literature, the most critical factor to the post-incident management phase is human error. However, no structured datasets record the crew’s actions during an incident and the human factors that contributed to its occurrence. To overcome the limitations mentioned above, we decided to utilise the unstructured information from accident reports conducted by governmental organisations to create a new, well-structured dataset of maritime accidents and provide intuitions for its usage. Our dataset contains all the information that the majority of the marine datasets include, such as the place, the date, and the conditions during the post-incident phase, e.g., weather data. Additionally, the proposed dataset contains attributes related to each incident’s environmental/financial impact, as well as a concise description of the post-incident events, highlighting the crew’s actions and the human factors that contributed to the incident. We utilise this dataset to predict the incident’s impact and provide data-driven directions regarding the improvement of the post-incident safety procedures for specific types of ships.
Highlights
According to the European Maritime Safety Agency, thousands of people were injured and hundreds died in marine accidents during the last decades, indicating the importance of safety onboard [1]
We provide a high-quality dataset that combines attributes such as the ship’s technical characteristics, the weather conditions, a description of the accident including the crew’s actions applied in the postincident phase, the human factors that contributed to the incident, and the attributes related to the environmental/financial impact of each incident
We describe the framework followed by domain experts to convert all the unstructured information in accident reports into a structured format
Summary
According to the European Maritime Safety Agency, thousands of people were injured and hundreds died in marine accidents during the last decades, indicating the importance of safety onboard [1]. These data are in text format (i.e., reports), and their further usage requires the prior process of extracting this information Creating such structured datasets for marine incidents is challenging, and there are many restrictions to the use of the already existing ones [2]. We provide a high-quality dataset that combines attributes such as the ship’s technical characteristics, the weather conditions, a description of the accident including the crew’s actions applied in the postincident phase, the human factors that contributed to the incident, and the attributes related to the environmental/financial impact of each incident. To the of our knowledge, this is the first time a dataset includes characteristics related to the accident’s conditions (e.g., weather, cause, etc.), the post-incident management process (e.g., successful/failed evacuation of the ship, the crew actions, etc.), the human factors that contributed to each incident’s occurrence, and the corresponding environmental/financial impact.
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