Follow the Money
The Follow the Money data model is designed to organise concepts which arise in money laundering and corruption investigations in a way that is useful to investigative journalists.
Follow the Money is both the name of the data model, and of a command-line tool used to generate and process data formatted using this model. Aleph is an interactive viewer on top of a search index of Follow the Money entities.
This page only provides a high-level overview of the data model. Check the reference documentation for in-depth explanations.
The data model of Follow the Money consists of so-called schemata, i.e. object types. They exist as an inheritance hierarchy, rooted in things and intervals. You can also think of these as entities and events.
Things describe most of the real-world objects represented in Aleph and Follow the Money. This includes People and Companies, Assets and Court Cases. While normally generated by the file ingestion service of the Aleph server, a large set of sub-types of Documentis creating through entity mappings.
Intervals are business interests, court cases, sanctions and transactions (and their descendents). Intervals tend to be useful for linking two entities together, possibly over a specific time period.
To explore the Follow the Money schema hierarchy in detail, check the FollowTheMoney schema defintions.
Follow the Money is reminiscent of a linked data ontology, and indeed it is regularly published in Turtle and RDF/XML format for use in RDF-based applications. See the ftm export-rdf documentation for help on how to export Follow the Money data to linked data.
In conjunction, you can use the RDF-based ontology version that is generated here. It can be used to drive interactive data explorers in multiple formats, including:
The LODE documentation browser (great for reading)
A network visualisation of the ontology provided by WebVOWL.
Any user of Aleph should feel free to propose changes or extensions to the Follow the Money data model by submitting a GitHub issue. Proposed changes should embody the design sense of the data model, which prioritises practicality over correctness; understandability over standards compliance.
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