Knowledge base structure

The structure of a knowledge base can vary depending on the tool used. However, since this guide is based on CogniVis, we will describe its structure in this lesson.

Knowledge Base as a library with shelves

The best way to imagine our knowledge base and its structure is as a library. I mean a classic, physical library, with wooden shelves and paper books.

CogniVis Docs (the CogniVis module responsible for the knowledge base) is a digital representation of a physical library.

When you open it, you'll see... shelves.

Each shelf corresponds to a specific segment of corporate knowledge, such as marketing, IT, design, and so on. This is, of course, just an example division, and each organization should adapt this structure to its own needs.

Books

Then, when we enter a shelf, we are presented with... books.

Books are smaller elements of a given segment of corporate knowledge (i.e., a given shelf). For example, entering the "Marketing" shelf, we might find books like "SEO," "Social Media," or "Branding." Each of these books contains more specific information about a segment of corporate marketing knowledge.

Chapters

Just like in physical books, here we also find chapters. For example, entering the "Social Media" book, we would see two chapters inside:

1. General Guidelines
2. Graphics

Chapters are simply a smaller unit of our library's structure and are embedded directly in books.

Pages

The smallest unit of the knowledge base structure is pages. They are embedded in chapters (although they can also be directly embedded in books).

In the image below, elements marked in blue are pages, and those in orange are chapters to which they belong.

Each page is simply an individual document with a classic text editor.

In summary

The structure of the CogniVis Docs knowledge base is simple. If we imagine it as a library, the schema looks as follows:

Library > Shelves > Books > Chapters > Pages

Based on our tests, we've concluded that this structure is best for both humans and artificial intelligence. It provides an appropriate level of complexity and embedding of documents to maintain order, while preventing overly complicated nesting that could reduce its readability and ease of use.