Fractal Knowledge was an early attempt at structured knowledge representation that combined metadata and human-readable content. While successful in some aspects, its limitations in flexibility led to the development of the more adaptable Human Knowledge Markdown approach.
Fractals are geometric shapes using simple rules to create intricate details that repeat when you zoom in or out.
Fractal knowlege explores how simple rules can be applied to knowledge to create equally intricate structures of interlinking knowledge repositories. So fractal knowledge is both:
- Sets of rules defining how to store and link notes
- Knowledge saved using a set of rules
With this approach, two or more people that agree on a set of rules can share repositories of knowledge and have them automagically link together.
As a proof of concept, fractal knowlege defines and uses the fractal knowledge core ruleset. It describes how to store, tag, and link notes together in simple topic structures. You can follow it to pull this repository directly into your knowledge set, and then create your own repositories of knowledge for sharing in the same format.
Current experiments include
- Many note types. Like a person, team, company, meeting, journal, recipe, and so on.
- Scaling. Knowledge might take the form a line, section, note, topic, or repository. Different "sizes" of knowledge should still behave in similar ways.
- Incorporating tasks. Rules for tracking stuff like books read or movies watched, so they're kept in consistent, easy-to-query formats.
Creating a common format for sharing notes and knowledge is not an easy task, but a successful one would offer new ways to extend knowledge management systems. The core ruleset is meant as the simplest possible set of rules that creates sharable knowledge. Ideas that both simplify it and extend it to more complex levels of sharing are welcome.
