Dataharvest 2026 - the European Investigative Journalism Conference

Investigace.cz has been monitoring TikTok in the Czech Republic for foreign influence operations for several years. and has learned to track the Czech TikTok space systematically.

In this hands-on session, they will share the lessons learnt with the participants:

-How to use scraping-as-a-service tools to collect TikTok data without coding
-How to decode TikTok URL hashes to extract hidden metadata (such as exact publication timestamps)
-How to work with the TikTok Research API
-How to think beyond simple metrics (views, likes, followers) and understand what TikTok data can and cannot tell you about influence operations

Participants will leave with practical skills and a realistic understanding of the limits of TikTok analysis. One doesn't need to be a data journalist to attend this session, but an understanding of how scraping works and basic data skills will be helpful!

Much of modern life is mediated through phones and apps. To investigate anything they touch, you need to understand where these apps' data comes from, what they're sharing, and with whom. But while network forensics & scraping for the web have received plenty of attention, the same isn't true for mobile, where techniques can be more challenging and clear guides are harder to find.

In this talk, we'll take a hands-on look at how HTTP Toolkit and other tools make it possible to easily capture, inspect & modify network traffic on mobile. We'll explore real-world examples of these techniques in data journalism, and you'll learn how you can use this to extract the datasets that power mobile apps, expose privacy leaks & security issues, and investigate exactly how apps do what they do.

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.

This session is based on a case from Serbia, where we managed to identify a person whose identity Serbian authorities and pro-government media actively tried to hide. Starting from a blurred face in a leaked video, we combined basic OSINT with business registries, social networks, geolocation, face recognition tools, dark web email searches, and simple AI-assisted image analysis. We will walk the audience through each phase of the process,  and explain what worked, what failed, and how one can verify findings when evidence is being altered or erased in real time.

Attendees will leave with a practical workflow they can reuse in their own investigations: how to move from a fragment of visual evidence to a confirmed identity, how to cross-check business data with social platforms, how to use face search and morphological comparison safely, how to track digital behavior after supposed arrests, and how to document disappearing online traces before they are wiped. The goal is to share a method that can travel across borders and work in any country where power structures try to keep people invisible.

According to the OECD, 79% of companies use algorithmic management tools to automate recruitment, manage human resources and, above all, monitor and control workers. Subjected to constant algorithmic surveillance, salespeople in all sectors are always aware that their every move is being scrutinized. In digital professions, particularly video game
design, this digital activity tracking fuels burnout and workplace suffering. Delivery workers, especially those on bicycles, face even more serious consequences: the accelerated pace of their work leads to serious workplace accidents and even death. In France, the press has documented more than twenty fatal accidents since the arrival of Uber 
Eats and Deliveroo to the market in 2015.

How are these technologies deployed? How can we bypass corporate communications to document their real impact? How can we identify the hundreds of small businesses worldwide that market these devices? In this session, Clément Pouré, who has published around fifty investigations on workplace surveillance in the Age of AI, and a book on the same topic, will shed light on the surveillance practices of numerous multinationals such as McDonald's and TP (a world leader in call centers), but also on the more insidious practices of smaller companies across all sectors.

In this session, we'll briefly look into the history of workplace surveillance and its impact on employees, and chart an overview of the current technologies and the risks they represent. We will review the methods and sources that can be used to investigate the subject. The session is suitable for beginners, and no prior experience in algorithmic investigations is required to attend.