MAIB Data Portal updated with 2025 data January 2026

The Marine Accident Investigation Branch (MAIB) has refreshed its public Data Portal with 2025 data, published on 20 January 2026. If you work with maritime safety, study transport, or simply care about how risks at sea are tracked, this is a good moment to learn how the portal works and why figures sometimes move after an update. (gov.uk)

A quick reminder of who MAIB is: it is an independent unit within the Department for Transport that investigates marine accidents to improve safety, not to apportion blame or establish liability. Each year it receives roughly 1,500 to 1,800 reports and begins about 30 investigations, publishing reports and recommendations to prevent repeat incidents. (gov.uk)

What you can access today is practical and built for learning. There is a prepared, filterable dashboard for quick views of anonymised accident data, three downloadable CSV tables designed to link together, and a Power BI (.pbix) file that mirrors the online model for deeper analysis. The service says releases are republished twice a year and notes the dashboard itself has no download button-screen capture is fine if you need a snapshot. (maps.dft.gov.uk)

The CSVs are straightforward. ‘Occurrences’ lists each reported event with severity, location and a short description. ‘Vessels’ describes each craft involved, including category and damage. ‘Affected Persons’ records injuries and fatalities with anonymised details. Start with Occurrences for counts, then join to Vessels or Affected Persons if you need vessel‑level or person‑level detail. (maps.dft.gov.uk)

Linking the tables is the step that turns raw rows into solid analysis. The MAIB guide sets out the unique keys: Occurrence_Id identifies an event; Vessel_Profile_Id identifies a vessel within that event; Affected_Person_Id identifies an individual linked back to both. Using these keys, you can build one‑to‑many relationships cleanly in your chosen tool. (maps.dft.gov.uk)

Prefer a ready‑made route? Download the MAIB Power BI dataset file. It opens in Microsoft Power BI Desktop, which is a free download from Microsoft. The file already contains the model, so you can filter, visualise and export your own charts with minimal setup; installing the current 64‑bit Desktop version is recommended. (maps.dft.gov.uk)

When you open the downloaded Power BI file, you will see an ‘MAIB Overview’ page with headline counts and time trends, a map of all occurrences, and pages for each broad vessel group. Use the ‘Filter the Data’ control to narrow results and ‘Clear Filters’ to reset. It’s a friendly way to learn the field names before you code. (maps.dft.gov.uk)

A few data‑literacy notes help you read the numbers fairly. Where the exact accident day is not confirmed, the date is rounded down to the first of the month. Vessel lengths and tonnage are rounded to two significant figures. If there is a published investigation report, short descriptive fields may be blank; some non‑UK cases carry redactions. What this means: totals are robust, but narrative text may be limited by design. (maps.dft.gov.uk)

Expect revisions as part of responsible publishing. The portal draws checked extracts from MAIB’s live COMPASS case management system and records can change as investigators add details-so your chart from last year may not match today’s totals. The GOV.UK notice also flags that previously published numbers may differ after new information comes to light. (maps.dft.gov.uk)

Try this as a class or team exercise: use the online dashboard to explore a vessel category you know-say, fishing-and note the trend in injuries by year. Then download the CSVs and recreate the same view in your spreadsheet or statistics software, joining on the keys. You’ll practise reproducible methods and see where definitions and rounding affect your totals.

Finally, remember what these numbers are for. MAIB investigations and reports aim to prevent future accidents, not determine liability, and MAIB evidence is handled carefully in court. When your analysis throws up questions, pair the data with the published reports to understand context and safety lessons before drawing conclusions. (gov.uk)