Raw data conveys accuracy but offers little immediate practical value.
Lead with the key question, then practical relevance, then deeper analysis.
Choose a few key metrics and place them in context.
Each article answers a clear operational question.
EMSA publishes data through various channels: EMCIP (European Marine Casualty Information Platform), THETIS (for PSC inspections), SafeSeaNet and the annual EMSAFE report. Each of these sources has its own structure, classification system and limitations. For editorial processing, understanding these differences is essential.
EMCIP data capture maritime accidents and incidents according to IMO categories: very serious casualty, serious casualty, less serious casualty and marine incident. This classification determines which cases are subject to mandatory investigation and at what level of detail. For an editorial article, it is important to make this gradation transparent — a rise in “less serious casualties” has a different operational significance than a rise in “very serious casualties”.
THETIS data on PSC inspections are structured by deficiency codes. Each code references a specific international convention (SOLAS, MARPOL, MLC, ISM) and a concrete requirement. For editorial use, these codes offer the opportunity to analyse trends by subject area: are fire protection-related deficiencies rising? Are MLC-related observations increasing? Where are the most frequent grounds for detention?
The decisive step in the translation is contextualisation. Raw figures are of little significance to most readers. The question “What does this number mean for my operations?” must be answered in the article. This requires not only statistical competence but operational understanding: why are certain deficiency categories particularly problematic? Which practical measures reduce the risk?
The editorial process can be divided into five steps. First: identify the source and verify data quality. Not all EMSA datasets have the same coverage and currency. Second: formulate the core question. What is the one question the article answers? Third: select relevant data points. Less is more — three meaningful metrics are more effective than twenty. Fourth: contextualise. What do the figures mean for the superintendent, the technical manager, the HSQE head? Fifth: derive a recommendation for action. Every article should conclude with a concrete recommendation.
A common mistake is data overload. EMSA reports contain vast quantities of data. The temptation to pack as much as possible into one article produces texts with the same readability as the original report — that is, none. The editorial achievement lies precisely in reduction: from a hundred data points, identifying the three that are most relevant for the target audience.
Visual presentation supports readability substantially. Trends over time, comparisons between vessel types or flag states and the highlighting of outliers can be displayed in simple charts. The important thing is that visualisations convey a clear message rather than serving as decoration.
The same EMSA data can be processed differently for different target audiences. For superintendents, operational relevance takes precedence: which deficiency categories affect my vessels? Which maintenance priorities do I derive from this? For managing directors and fleet directors, the strategic contextualisation is more important: how is my fleet's risk profile developing compared to the industry? Where must I invest?
For HSQE managers, the emphasis lies on compliance trends and the development of regulatory focus areas. When EMSA data show that certain flag states are subject to increased controls or that certain deficiency categories lead to more frequent detentions, this has direct implications for PSC inspection preparation strategies.
This differentiation by target audience makes it possible to create multiple articles with different focus areas from a single EMSA dataset — without becoming redundant. The same base dataset can be processed as an operational practice article, a strategic analysis and a compliance briefing.
Not every EMSA publication justifies a dedicated article. Three criteria help with the assessment. First: does the dataset contain a surprise or does it confirm a trend? Both are editorially usable — surprises generate attention, trend confirmations strengthen recommendations for action. Second: is there a current occasion that makes the data particularly relevant? New regulation, technological changes or current casualty series increase relevance. Third: can the article provide added value that the reader would not extract from the original report themselves?
When all three criteria are met, a high-quality specialist article results. When none applies, it is more honest to forego the article than to reproduce data without added value.
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