TreeBase

The design pattern for intelligent & collaborative & long-term knowledge bases.

TreeBase

TreeBase is a design pattern for growing collaborative, limitless knowledge bases that get better with age.

In TreeBase you create one file per concept and fill that file with richly structured plain text data. TreeBase uses Tree Notation syntax, so there is no noise introduced by the syntax, and you can store any and all kinds of data structures, and every word is strongly typed. TreeBase uses Git for version control so collaboration, auditing, and decentralization come built in.

Are there some demo TreeBases?

When should I use TreeBase?

TreeBase helps you build knowledge bases about anything. It doesn't matter how simple or complex the domain. TreeBase is useful whether you are building a knowledge base by yourself or with thousands of people.

What are some TreeBase Implementations?

TreeBase is more of a design pattern than a software application. However, the JTree TreeNotation SDK contains a lot of tools useful for working with TreeBases.

How does it work?

In a TreeBase you store data in plain text files using TreeNotation. Instead of storing data in rows in a compressed binary format, you store data in regular files. So a database of planets might look like this:

📁planets venus.planet mercury.planet earth.planet mars.planet jupiter.planet saturn.planet neptune.planet uranus.planet

Each file contains information in a schema that you specify in a Grammar file. For example, the file `mars.planet` might look like this:

diameter 6794 surfaceGravity 4 yearsToOrbitSun 1.881 moons 2

The Grammar file (TreeBase's version of "Schemas"), for this file would be this:

planetNode root todo Change pattern to postfix. pattern \.planet$ inScope abstractIntPropertyNode abstractFloatPropertyNode catchAllNodeType errorNode anyFirstCell todo remove the need for this errorNode baseNodeType errorNode intCell highlightScope constant.numeric.integer floatCell highlightScope constant.numeric.float keywordCell highlightScope keyword abstractIntPropertyNode cells intCell firstCellType keywordCell abstract abstractFloatPropertyNode cells floatCell firstCellType keywordCell abstract surfaceGravityNode extends abstractIntPropertyNode diameterNode extends abstractIntPropertyNode moonsNode extends abstractIntPropertyNode yearsToOrbitSunNode extends abstractFloatPropertyNode

TreeBase delegates to Git for versioning, backups, and collaboration.

Do I need to use a library to use TreeBase?

No. You can use the TreeBase system without installing any new software on your computer. In fact, you don't even need to use a computer at all. Pen, paper, and some folders work well for small TreeBases.

Can I use TreeBase with my existing SQL databases?

Yes. With one command you can turn any TreeBase database into a SQL database. There is no lock-in.

Can I use TreeBase with my existing JSON or CSV workflows?

Yes. With one command you can convert any TreeBase into JSON, CSV, TSV, etc. There is no lock-in.

Can I use TreeBase with a CMS?

Yes. TreeBase works great with Scroll. In a TreeBase + Scroll pattern, each entity gets it's own page. Your grammar simply extends Scroll's grammar.

Does TreeBase scale?

For collaborative knowledge bases, yes. We have been using TreeBase for over 2 years in systems with millions of lines and dozens of collaborators.

At the moment TreeBase works best for knowledge bases of less than 100,000 entities/files (each file can have many facts). For larger TreeBases you are likely to hit some scaling challenges. Read more on that here.

Our focus with TreeBase is on collaborative knowledge bases, like Wikipedia for data. You are free to experiment with using TreeBase in other domains, and if you do please let us know how you are using it, but at the moment our focus is on knowledge bases.

How is this different than Wikipedia?

You can think of TreeBase as similar to the MediaWiki system that powers Wikipedia. The difference is whereas Wikipedia is focused on narratives first and semantic facts second, TreeBase is focused on semantics first and narratives second.

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