Enron 2020 is a collection of E-Discovery scripts and research that is designed in order to undertake practical research on effective methods of e-discovery in Python and handling large fraud based datasets. Goals of this project include:

• Scripts that assist in E-Discovery of the enron corpus
• Examples of E-Discovery interfaces and tools
• Optimisation of large document processing tasks

These are initially stand alone Python scripts to be converted into an MVP to prove the functionality of the "E-Discovery Analysis Techniques for Large Email Datasets: An Analysis of The Enron Corpus" report that is our project for the Enron 2020 project.

We will constantly be using plugins and libraries to extend the function of our project. Python being the language of choice it is imperitive that we list all libraires and purposes.

If changes are material, please consult the team and have a secondary approver for the commit. Slight change management process to follow, unless there is am emergency change that needs to take place, get someone else to approve your commit. Good manners when merging and commiting stuff.

• Integrate lessons learned from FreeDiscovery @ https://github.com/FreeDiscovery/FreeDiscovery
• Add interfaces to show off tools and scripts to a non-technical audience
• Develop report further so that techniques and scripts complete intented objectives

MIT