Early in December 2013 a lawfirm began to send out approximately 10 to 40 thousand cease-and-desist letters on behalf of the rightholder of a bunch of porn flicks for streaming those films on redtube. So far, so good. Now a lot of people didn’t like to receive bills ranging from 250 to more than a thousand Euro for streaming erotica just before christmas especially when being pretty sure that they didn’t even do so. Now given the magnitude of this case a lot of these people turned sour and started to dig a bit deeper. And what was brought to light is a shady network of companies with links where there should be none and a bunch of business partners who as well turned out to have more in common than what was to be seen at first glance.
A need for structure
It was amazing to observe how the digital public managed to dig up details and links so that even before police or justice moved a little finger the whole affair was already pretty much exposed as a scheme. But only to those who managed to keep track of all the updates and where those would be published – on a countless number of blogs, forums and comment sections. At some point somebody realized this pool of data needs to be put into a structure and took the effort to turn it into a handy graph providing references.
Visualizing patterns for purpose of investigations
The nature of those investigations is mostly comprised of finding patterns in events and bringing links and link paths between entities to the light of day. Who knows who from where and when did what happen when and how does this relate to you name it. And to organize this process in a transparent and collaborative fashion, tools are needed which should be easy to employ even by people who are not very competent using advanced technology but for whatever reason very motivated to participate in the investigations.
So I sat down and programmed a little tool as a first step to simplify structuring information in a team-based process. And this is how it looks so far (version 0.0.0):
At this point the tool – which I baptized “inter-conn” for lack of a better name – can link nodes and events. Go ahead, give it a try! The visualizations are based on CSV structured texts located within the “data input” section. The CSV can be edited there or loaded from local files. One reason why I chose CSV as the data structure is because it is intuitive and easy to edit manually.
Simply download the three files “nodes.csv“, “links.csv” and “events.csv” and load them using the facilities on “data input” tab. Finally click [play] and you should see something colorful on the “visualization” section. You can also edit the CSV of course to add new nodes, links and events. (Don’t forget to click [play] after you are done.) Some clarifications regarding the data format you will find on the GitHub project homepage.
Clicking on the calendar will show you details on events associated with the respective month, on a link will display information on that. The colors of links and nodes are determined by their type – “human”, “firm”, “thing” for nodes and “known”, “guesswork” for links. It’s that simple.
I am still amazed about how easy it is to program an intuitive and vivid UI with d3.js and jQuery. I am a bit worried about the layouting of the UI – I hope it is not too messed up for users with very different screen estate. In case you encounter a bug, something is unclear or you have a feature suggestion for future versions you are welcome to contact me. Having said that, the app is on GitHub for a reason – fork away.
I plan to rewrite and enhance this app in context of another German criminal case which I personally consider as way more important. I am talking about what’s happened and is happening to Gustl Mollath and the surrounding conincidences in connection with the affair. The lawsuit will be reopened in summer and a lot of people have already collected together heaps of truly facinating details just waiting to be nicely visualized to make structures obvious – because a chart is worth a thousand words.
(original article published on www.joyofdata.de)