This session provides a practical guide for using Automatic Identification System (AIS) data to investigate maritime irregularities. Our case study will be the Russian shadow fleet. The session is beginner-friendly, while the second case study will also be interesting to advanced AIS users and people with programming skills.
In the course of the session, we will present two case studies demonstrating how AIS data can be used to investigate the Russian shadow fleet.
The first case study will show how to use AIS data and vessel metadata to evaluate the environmental risk of shadow fleet traffic. The second is a recent investigation of Greenpeace Italy exposing a new ship-to-ship (STS) transfer hub off the coast of Sicily, revealing multiple sanctions breaches and a lack of oversight by Italian authorities. The investigation triggered two parliamentary inquiries and an investigation by the Chief anti-Mafia Prosecutor and was reported on extensively across national media.
This case study will showcase how the automatic STS detection in MarineTraffic, combined with network analysis (JavaScript, Gephi) and OSINT sources, can be used to trace chains of transfers that bring Russian oil into European ports.
Our session will offer a pro user's look into different proprietary and open-source AIS data platforms and evaluate their affordances (e.g., data export options, alerts, analytics functions), both with and without login. We will give an overview of additional data sources to cross-validate and enrich AIS data (Equasis, ITF Seafarers, IMRRA, order books, class society databases, IGPANDI) and share an internal tool we developed to access these sources automatically.
Participants will leave with practical knowledge of which AIS platforms to use for specific investigative needs, what open-source alternatives exist, and how to apply these tools in combination with network analysis and OSINT sources to uncover maritime irregularities.
The BBC Shared Data Unit wanted to generate a map image for each authority in the UK showing the state of flood defences in that area — so they turned to the mapping tool QGIS’s built-in Python functionality.
In this session, you will learn how to generate and export dozens of maps in QGIS centred at different points, and how AI can help speed up the process.
To follow along, participants should have some basic knowledge of QGIS and be comfortable using Python or vibe coding.
After attending this session, participants should be able to understand how Python works in QGIS and use AI to help generate, understand, and adapt code. Participants should have QGIS and Python installed on the computer (qgis.org/download + python.org/downloads) and a free account with an AI tool such as ChatGPT, Gemini, or Claude
Journalist and Academic, BBC/Birmingham City University
Paul Bradshaw runs the MA in Data Journalism at Birmingham City University and also works as a consulting data journalist with the BBC Shared Data Unit. A journalist, writer and trainer, he has worked with news organisations including The Guardian, Telegraph, Mirror, Der Tagesspi... Read More →
Ioanna Petsiou is an investigative data journalist working across data analysis, satellite imagery, and mapping to uncover and explain complex stories. She is particularly drawn to environmental reporting and to building clear, reproducible ways of working with data that others can... Read More →
