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This repository contains a pragmatic data model for the entities most commonly used in investigative reporting: people, companies, assets, payments, court cases, etc.
The purpose of this is not to model reality in an ideal data model, but rather to have a working data structure for researchers.
followthemoney
also contains code used to validate and normalize many
of the elements of data, and to map tabular data into the model.
For a general introduction to followthemoney
, check the high-level introduction:
Part of this package is a command-line tool that can be used to process and transform data in various ways. You can find a tutorial here:
Besides the introductions, there is also a full reference documentation for the library and the contained ontology:
There's also a number of viewers for the RDF schema definitions generated from FollowTheMoney, e.g.:
For local development with a virtualenv:
python3 -mvenv .env
source .env/bin/activate
pip install -e ".[dev]"
Now you can run the tests with
make test
We release a lot of version of followthemoney
because even small changes
to the code base require a pypi release to begin being used in aleph
. To
this end, here's the steps for making a release:
git pull --rebase
make build
make test
git add . && git commit -m "Updating translation files"
bumpversion patch
git push --atomic origin main $(git describe --tags --abbrev=0)
This will create a new patch release and upload a distribution of it. If
the changes are more significant, you can run bumpversion
with the minor
or major
arguments.
When the schema is updated, please update the docs, ideally including the
diagrams. For the RDF namespace and JavaScript version of the model,
run make generate
.
FAQs
A data model for anti corruption data modeling and analysis.
We found that followthemoney demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 5 open source maintainers collaborating on the project.
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