How to Use JSON Schema to Validate Your Data

By JSONValidator.dev Team • 2025-07-04

What is a JSON Schema?

A JSON Schema is a standardized way to describe the structure, required fields, and value types in your JSON data. Think of it as a contract or blueprint for what valid JSON should look like. JSON Schema is written in JSON itself, making it both machine-readable and easy to edit.

JSON Schema is not just for validation—it's also useful for code generation, API documentation, and editor auto-completion.

Why Validate with a Schema?

  • Prevent bugs by catching invalid or missing data before it causes problems.
  • Enforce data consistency across different teams, apps, or APIs.
  • Generate documentation automatically from schemas.
  • Help editors and tools provide better auto-completion and inline help.
Even a simple schema can catch common mistakes, saving hours of debugging later.

A Simple Example: Basic Schema

Here's a basic JSON object, followed by a minimal schema that validates its structure:

{
  "name": "Alice",
  "age": 30
}
{
  "type": "object",
  "properties": {
    "name": { "type": "string" },
    "age": { "type": "number" }
  },
  "required": ["name", "age"]
}

This schema ensures that the object must have a 'name' (as a string) and an 'age' (as a number).

How to Write a Custom Schema

You can define advanced rules in your schema: restrict field values, define nested objects, or set minimum/maximum numbers. Here’s an example that validates an array of products:

{
  "type": "array",
  "items": {
    "type": "object",
    "properties": {
      "id": { "type": "string" },
      "price": { "type": "number", "minimum": 0 },
      "tags": {
        "type": "array",
        "items": { "type": "string" }
      }
    },
    "required": ["id", "price"]
  }
}
Start small: build your schema as you go, and use online validators to check each step.

Using JSONValidator.dev for Schema Validation

  1. Paste your JSON data in the main editor.
  2. Paste your JSON Schema in the schema editor below.
  3. Click Validate JSON Against This Schema.
  4. Review validation results, with any errors highlighted and explained.
All validation happens in your browser—your data never leaves your device.

Troubleshooting Schema Validation Errors

Common reasons for validation errors include:

  • A required field is missing from your data.
  • A value type does not match the schema (e.g., string vs. number).
  • The schema itself is invalid or contains typos.
Carefully check error messages—they’ll often tell you the exact field and type mismatch.

Conclusion

JSON Schema validation is a powerful way to make your data robust and error-proof. Try creating a schema for your own data with our free JSON Schema Generator and validate it live!