Data Models are schemas that define the structure and validation rules for structured data assets in the Gateway Protocol. They ensure data consistency and provide a standardized way to validate and organize information.

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Understanding Data Models

Before working with structured data assets, it’s important to understand:

  • Data Models define the expected structure of your data using JSON Schema
  • Every structured data asset must conform to a Data Model
  • Data Models help maintain data quality and consistency

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Creating Data Models

Use the SDK to create Data Models that define the structure of your data:

import { Gateway } from "@gateway-dao/sdk";

const gateway = new Gateway({
  // your configuration here
});

const dataModel = await gateway.dataModel.create({
  title: "Employee Profile",
  description: "Standard employee information schema",
  tags: ["HR", "Employee", "Profile"],
  schema: {
    title: "Employee",
    type: "object",
    required: ["firstName", "email", "department"],
    properties: {
      firstName: {
        type: "string",
        title: "First Name",
        description: "Employee's first name",
        minLength: 2,
      },
      lastName: {
        type: "string",
        title: "Last Name",
        description: "Employee's last name",
        minLength: 2,
      },
      email: {
        type: "string",
        title: "Email",
        description: "Corporate email address",
        format: "email",
      },
      department: {
        type: "string",
        title: "Department",
        description: "Employee's department",
      },
      profilePhoto: {
        type: "string",
        title: "Profile Photo",
        description: "Employee's profile picture",
        contentMediaType: "image/png",
      },
      skills: {
        type: "array",
        title: "Skills",
        description: "Professional skills and competencies",
        items: {
          type: "string",
        },
      },
    },
    additionalProperties: false,
  },
});

console.log("Created Data Model with ID:", dataModel.id);

​
Data Model Structure

A Data Model consists of several key components:

  1. Metadata

    • title: Name of the Data Model
    • description: Detailed description of the Data Model’s purpose
    • tags: Array of keywords for categorization

  2. Schema

    • Follows JSON Schema specification
    • Defines the structure and validation rules
    • Supports various data types and validations

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Supported Data Types

Data Models support all standard JSON Schema data types:

  • string: Text data
  • number: Numeric values
  • boolean: True/false values
  • array: Lists of items
  • object: Nested structures
  • null: Null values

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Validation Rules

You can specify various validation rules:

const schema = {
  type: "object",
  properties: {
    // String validation
    username: {
      type: "string",
      minLength: 3,
      maxLength: 20,
      pattern: "^[a-zA-Z0-9_]+$",
    },

    // Number validation
    age: {
      type: "number",
      minimum: 0,
      maximum: 120,
    },

    // Array validation
    tags: {
      type: "array",
      minItems: 1,
      maxItems: 10,
      uniqueItems: true,
      items: {
        type: "string",
      },
    },

    // Format validation
    email: {
      type: "string",
      format: "email",
    },

    // Media type specification
    avatar: {
      type: "string",
      contentMediaType: "image/png",
    },
  },
};

​
Retrieving Data Models

You can retrieve Data Models using various methods:

// Get a specific Data Model by ID
const dataModel = await gateway.dataModel.get(modelId);

​
Best Practices

  1. Plan Your Schema

    • Design your Data Model schema carefully before creation
    • Consider future needs as schemas cannot be modified after creation
    • Include all necessary validation rules

  2. Use Required Fields

    • Specify required fields to ensure data completeness
    • Be conservative with required fields to maintain flexibility

  3. Validation Rules

    • Use appropriate validation rules to maintain data quality
    • Consider adding min/max lengths for strings
    • Add reasonable bounds for numeric values

  4. Documentation

    • Provide clear descriptions for fields
    • Use meaningful titles for properties
    • Add relevant tags for better discoverability

  5. Property Constraints

    • Consider setting additionalProperties: false to prevent extra fields
    • Use appropriate formats for specialized strings (email, URI, etc.)
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