How to Build Complex Database Searches Using Venn Diagrams

A method for searching databases by visually connecting Venn diagrams to represent complex logical relationships between different sets of data.

What it covers

This patent describes a way to make database searching more intuitive by using visual icons that resemble Venn diagrams. Instead of typing complex code or SQL queries, a user selects specific regions within these circular icons to define how different data sets should overlap or exclude each other. The system then takes these visual selections and the lines connecting them to build a formal search query that a database can understand. For example, a user could drag or resize parts of a Venn diagram to tell the computer to find records that are in 'Set A' but not in 'Set B', and then link that result to another diagram to further narrow the search.

What it doesn't cover

• —Does not cover text-based query languages like SQL or natural language processing.
• —Does not cover search interfaces that rely solely on keyword input fields.
• —Does not cover the underlying database storage or retrieval engine itself.
• —Does not cover systems that do not use visual icons to represent set inclusion properties.

The clever bit

The innovation lies in treating the graphical representation not just as a picture, but as a dynamic input method where gestures (like resizing or moving a circle) directly translate into logical parameters for a database query.

Why it matters

This patent was filed in 1996, a time when database searching was almost exclusively the domain of experts writing code. It represents an early attempt to democratize data access by mapping abstract Boolean logic (AND, OR, NOT) to familiar geometric shapes. It is highly cited because it anticipated the need for visual query builders in the burgeoning era of web-based data exploration.

Real-world examples

• 1.Visual query builders in business intelligence software
• 2.Advanced data filtering tools in research databases
• 3.Graphical interfaces for set-based data analysis