The examples above are live-you can play with them right on this page! PLDB.com and CancerDB.com are both powered by TrueBase.
Yes. We offer a paid complete white-glove service for moonshot problems. You can also email email@example.com for a custom quote.
TrueBase is a new kind of database designed from the ground up for trust. TrueBase is like Wikipedia but fully computable—the focus is on comparable data, not narratives. A TrueBase is a collection of files (rows and column schemas) that compile to a single giant table ("the model") that can answer questions in a data backed way. TrueBase is a way to build an "expert system" out of simple parts. A TrueBase model is fully human readable and auditable—there are no black box parameters.
TrueBase will benefit greatly from LLMs. First, they will provide a powerful and easy new way to query a TrueBase using natural language. Second, they will help experts building TrueBases add data, identify and fix mistakes, and even help improve the schemas of a TrueBase.
TrueBases may also help solve the "hallucination problem" in LLMs by providing trustworthy datatables that can be queried and referenced when answering prompts.
We live in an age of lies: of propaganda, advertisements, paywalls, trackers, licenses, proprietary formats, complected languages, patents—an information warzone. TrueBase is the database that makes no compromises on truth. Everything in TrueBase is designed to provide end users with an ever increasing amount of truth. Certain "scientific" fields are easily corrupted by money—we are designing TrueBase to mathematically solve these problems.
The cutting-edge option is to work from the demo PlanetsDB TrueBase:
git clone https://github.com/breck7/truebase cd truebase npm install . npm run local
Most people will want to use the Getting Started Guide. We are currently beta testing the Getting Started Guide. If you'd like to join the waitlist, please email firstname.lastname@example.org.
TrueBase helps people build the smallest expert models that can truthfully answer the most valuable questions.
TrueBase is very minimal. It's built on Tree Notation, a syntax-free notation that can support any data structure. The focus is on structured data (with a small amount of unstructured fields to help data editors). Because of this TrueBase allows for expert models that weigh-in at megabytes, not terabytes.
Traditional encyclopedias are weakly linked articles about things. Question sites are weakly typed narrative answers to user questions. TrueBase is different.
TrueBase is focused on computable structured data. We call this the "triangle of truth": Questions, Rows and Columns.
Everything starts with questions that people want to know the answer to.
To answer those questions, rows are added to the database. But it's not enough just to just list and describe the things.
In TrueBase columns are key. A typical TrueBase will add hundreds, to thousands, to tens of thousands of columns.
Our critical column theory is that to really reveal the truth it's just as critical to identify what we don't know and/or what's been purposefully left out. One byte of structured data can be worth more than a billion words of narrative. Especially in expert datasets with no easily repeatable results this is very important. For example, a database of academic studies might be harmful without a column indicating who paid for a study.
So in a TrueBase, it's just as easy to add a column as it is to add a row. Sometimes adding the right column can completely flip the answer to the question someone might have, or indicate that the question cannot yet be truthfully answered, more so than dozens of confirmatory columns.
Interconnectedness of the data is very important. When you put the effort in to integrate disparate data into one model, the resulting model is worth more than the sum of its parts. Not only does it become more useful because it's easier to compute over, but it also becomes increasingly difficult to lie as the size of a TrueBase increases due to the increasing number of logical constraints that the data would have to violate. A big TrueBase is hard to vary.
In TrueBase, you store your data in plain text files. This means your data is readily accessible—you can even view and edit it by hand.
You put your data in Tree Notation form. This means your data is all signal—no noise. This ensures you've minimized your data and made it as clean as possible, making it timeless. No matter what format you need your data in the future it will be perfectly preserved in the simplest form possible. You will never regret putting your data in a TrueBase.
A growing ecosystem of tooling makes it easy to augment your TrueBase with data from Large Language Models, web crawlers, and APIs, and run integrity checks, steadily making your TrueBase truer and truer.
You write your TrueBase schemas using the Grammar Language (a Tree Language) which enforces correctness, autofixes errors, and gives you tooling like autocomplete and syntax highlighting.
You can query your TrueBase using TQL (also a Tree Language).
You can display your data using Scroll (also a Tree Language).
So there are many pieces to the TrueBase system, but really just one thing to learn: Tree Notation. Your data, your query language, your schemas, your display language are all in these simple plain text Tree Languages.
Yes. TrueBase is public domain and is designed for public domain databases.
For large databases, TrueBase requires fast computers and fast SSD hard drives. TrueBase was not possible before the Apple M1s, which shipped in December 2020. Here is a post about early unsuccessful attempts at using TrueBase before Apple M1s.