a plain text file is the oldest idea for storing knowledge. see unix philosophy: "Write programs that do one thing and do it well. Write programs to work together. Write programs to handle text streams, because that is a universal interface."
;)
Thank you for the feedback. I've updated the paper with some more links.
The language in which the measures are written in (currently called Grammar. I will like rename it to something like Parssers) is quite advanced.
The improvements over Recutils, the closest precursor I am aware of, have now been added.
The PLDB ScrollSet is now about 500,000 cells of information. Each cell is strongly typed and fully auditable by git. There is a high amount of signal in that dataset. It is an intelligent set of weights, and continually getting more intelligent. And it is read at runtime as a single plain text file and compiled to a single CSV (or tsv, json, etc).
All from using the system documented in the paper (and the advanced language for Parsers).
If you can point me to a similar database or similar scale anywhere in the world (plain text base, >10e5 size, git backed, strongly typed, hierarchical and graphical), I would be grateful as I might learn something.