receipt-manegment - Ruby Software for When you Gotta Come with Receipts

This is a lil project that has an unfortunate reason for needing to exist.

What does this project do?

It contains ruby modules geared towards building and tracking evidence and files for the purpose of documenting and tracking files that may be used for evidence in formal and legal settings. Its totally amature but. I hope it'll be alright.

Some Things of note that We gotta do...

• Verity : We gotta build verity of files when we get them.

  • Mutability: Can this data change or not? Will it? Who did change it?
  • Collected data: Folders, Files, Logs all need to have verity built and tracked.
  • Attained data: Files and Things downloaded from the internet and not from devices or sources we control.
  • Scraped data: Documents and webpages that have been scraped.
  • Aligned data: The data that is created that unifies the content type must also be kept track of.
  • Written data: Gotta track the verity of files such as reports and such

• Uniform Data Rebuilding: Data has to be linted and then built into uniform and trackable methods.

  • CDR/Call Records: Gotta align calls with, timeline.

• Metadata : Gotta get as much of this as possible....

  • Source : Gotta log and document the sources and info related to attainment methods.
  • Processes : Whatever processing methods have been applied should be included.
  • Ref-Copies : Locations of Original copies
  • Verity : Any Verity settings or requirements
  • Manual data : Any manually set data such as stories or details about trust levels of the data or quality of sources.

• Timeline : Every event item that can be linted should also be placed along a timeline

  • Global timeline : Gotta have a global timeline built.
  • Incident timeline : Timelines of incidents
  • Chat timelines : This should include logs
    • Individuals : Timelines of various individuals.
  • Collection timelines :
  • Statute of limitations : Gotta track these if possible.

• Sanitization : We gotta remove any data from source material that may not be relevant or nessicary.

  • Non-relevant data : Such as debug or information that may be included in things that isn't helpful or relevant.
  • Data blinding : This means renaming and re-labeling information such as phone numbers so that they are easily identifiable as a unique label. Things such as changing phone numbers to an alias that obscures identifiable information to reduce exposure of things such as phone numbers, emails, addresses.
  • Personal data : Such as personal conversations that are not related to the documentation effort. Things like spam messages or communications that are desired to be kept private.