Exploring the Congo Holdup articles with Neo4j

As you may know, I am from Belgium. I love this little queer country, with all of its idiosyncracies and weirdness it still makes for a great place to live. Did I mention Beer, Waffles and Chocolate yet? Yes, that's why.

But in the 191 years that we have existed as a country, we have done some weird sh!t as well. As an example, we did some of the craziest stuff ever under our former King Leopold II. I got to know a bit more about that through Klara, a (Dutch spoken, but nevertheless crazy wonderful) Flemish radio station, which hosted a podcast about Leopold II's crazy, and sometimes cruel, adventures in Congo. See over here if you are interested. It's a terrible, but fascinating story.

So more recently, when I started reading about the Congo Holdup in De Standaard, the newspaper that I subscribe to over here, I could not be but interested - and wanted to know more. I have been reading about it on an off, and have made my way to the actual source of this investigation, which is run by the EIC - the European Investigative Collaborations - you can find the details over here. Essentially, this is a about How to rob a country, using a bank. Specifically, this is the BGFIBank, which laundered lots of unsavoury transactions through its books - and allowed some of the key leaders of Congo to get away with crazy big amounts of $$$ - leaving the country's citizens in poverty in their wake.

So this post is NOT going to be about the details of that investigation. It's more about how you can use a graph, and some of the easiest tools ever, to better make sense of a pile of articles like that. That's what I have tried to do, and what I would like to highlight below. I will leave the actual interpretation of this data to others.

Using Apache Zeppelin with Neo4j to analyse the FinCEN Files

Last week, we got another great and widely publicised case of Graph Databases' usefulness throw our way. The ICIJ published their FinCEN Files research, and on top of allowing you to explore the data on their website they also published an anonymised subset of the data as a series of CSV/JSON files. My friends and colleagues Michael Hunger, Will Lyon and the rest of the team, helped with the process of making this subset available as a Neo4j database (see this github repo), and there's even a super easy FinCEN Files Neo4j Sandbox that you can spin up in no time for some investigation fun.

So of course I had to take this data for a spin myself - it seems really important to me that more eyeballs are looking at this, and more people exposing the sometimes very questionable behaviour of the world's largest financial institutions.

Introducing Zeppelin

I had heard of some great technology a while ago that would allow people to use their data in a very different way, by looking at these interactive webpages that would interact with a Neo4j database.

Working with the ICIJ Medical Devices dataset in Neo4j

Just last weekend our friends at the ICIJ published another really interesting case of investigative journalism - tracking down and publishing the quite absurd and disturbing practices of the medical devices industry. The entire case with all of the developing stories can be found at https://medicaldevices.icij.org/ - take a look as it really is quite fascinating. Of course that meant that I wanted to see what that data looked like in Neo4j, and if I could have a play. I didn't have time for a full detailed exploration yet - but hopefully this will also give others the opportunity to chime in. So let's see.

The Medical Devices dataset as a graph

This turned out to be surprisingly easy. Just download the Zip file from the ICIJ website: https://medicaldevices.icij.org/download/icij-imddb-2018-11-25.zip, unzip this, and then we get 3 comma-separated-values files:

• one for the Devices that are being reported on
• one for the Events that are being reported (whenever something happens to a device (eg. a recall) then that is logged and reported)
• one for the Manufacturers of the medical devices.

That's easy enough.