Dataharvest 2026 - the European Investigative Journalism Conference

In our digitally connected world, perpetrators feel so safe online that they build their networks openly: on public-access porn websites and messenger apps such as Telegram. Our investigation for STRG_F/NDR in Germany uncovered an international rape network that had formed on porn websites and in dozens of private chat groups on Telegram. One group had more than 70,000 members.

Users exchange detailed information on how to drug and rape women who are already close to them, such as their wives, girlfriends, sisters, or mothers, without them noticing. The rapists share videos and photos of the assaults online. One man from Germany drugged and raped his wife for more than 15 years and generated millions of views with the footage. Our investigation triggered a police investigation, and he was stopped.

We'll share how we began investigating these networks, how we gained access to them, how we investigated the users for years by also going undercover, what tools we used, what ethical and moral challenges we have faced, and how we kept an overview of all the footage we documented and saved over the years.

We will address:
- How do you conduct online research in criminal networks? (Structures, dynamics, and mechanisms)
- How do you gain access to them?  (User's communication and behaviour) 
- What opportunities and limitations did we encounter? (Laws and journalists' rights, ethical and moral responsibilities)
- When should you consider undercover research, and what can it look like? (Journalistic standards and guidelines)
- How do you protect your own mental health when confronted with disturbing content?

The Great Firewall, censorship, and language barriers make open source research on China really difficult, if not impossible. In this session, we aim not only to make you aware of obstacles you may face, but to show you solutions and strategies, especially for journalists and researchers working from outside China who don't speak the language.

We’ll show you the research resources, toolbox and we'll share tips on:

1) how to navigate Chinese social media: WeChat, Douyin, Rednote and others,
2) how to reconcile information inconsistencies in English and Chinese,
3) how to read the ownership of Chinese companies: private, state owned and central government enterprises,
4) mobile device setup and translation applications.

This talk will show the methodology behind The Guardian’s exclusive investigation into properties advertised as tourist destinations on Airbnb and Booking.com located in Israeli settlements that are illegal under international law. The Guardian found 760 rooms being advertised in hotels, apartments, and other holiday rentals in illegal Israeli settlements in the West Bank, as NGOs and activists warned that these companies are violating international law and profiting from war crimes.

In their investigation, they used geospatial tools, like PostGIS and QGIS, to localise accommodations on a specific geographical area, and to join these accommodations with shapefiles representing the borders of illegal settlements to identify those based within settlement boundaries. Using OSINT methods and Google Sheets, they designed a methodology to solve data challenges like duplicate and multi-platform listings, and listings with approximate locations.

In this session, attendees will come up with a robust methodology to find tourist accommodations in any geographical area, so they can reproduce the method for new stories.

Tampermonkey is an age-old browser extension that allows you to inject scripts and stylesheets into any web page, turning the web into your personal playground. We'll look at how to customize your CMS with DIY features, add "Download all" buttons to paginated websites, automate tedious processes like filling out forms and redesign websites however you'd like. Best of all, Tampermonkey scripts are saveable and sharable, allowing you to give other members of your newsroom superpowers without fiddling with distributing extensions or asking them to run Python scripts. To follow along, participants should be able to install extensions in their web browser of choice.

Materials: https://jsoma.github.io/workshop-tampermonkey/

With so-called low-code platforms like n8n, you can quickly click together programs that would otherwise require tedious Python coding. And you can integrate LLMs at various points to, for example, extract information from texts or summarize content. This allows you to build complex workflows. Receive a Teams message from an agent when a nearby river level approaches extreme values? No problem! Automatically monitor the police website for accident reports and generate suggestions for brief news items? With n8n, this can be automated quickly. This workshop provides an introduction to the free platform n8n. No prior knowledge is expected.

Materials: https://github.com/chesselingfm/dataharvest26-n8n

Police work is notoriously difficult to investigate. While police actions directly affect fundamental rights and guide politics and law-making, official data on their influence is scarce.

In this session, we will share some tools and methodologies on how to investigate the police sources. We will draw on more than ten years of investigations into different aspects of police violence and state abuse of power in Germany. We will also show how the data-driven journalism tools can help to make the underlying structures more visible, and present our recent investigation into police unions in Germany: who they are, want they stand for and how they influence the public debate and politics. We pieced together data from different sources and combined it with investigative journalism to draw the full picture.

We want to show how it is possible to do a data-driven investigative story despite missing data. We will focus on the following questions:

- How to build your own datasets when no official statistics exist? Which public data sources about the police are available? Which data can we get from ministry inquiries? What about social media?
- How to clean up, classify and analyze the data? Which tools are helpful in combining manual and automated workflows?
- How to tell a complex data-driven story without this one headline? What are judicial and editorial hurdles when publishing a sensitive topic?
- What can investigative and data journalists gain from close collaboration? What worked well? What would we do differently?