Databus Gitbook
Databus
Databus
  • Overview
  • Guides
    • Data Publishing
    • Data Download
  • Use Cases
    • Data Version Control
    • Populating Database with Data
    • Data Quality Control
    • Data Crawling
    • Automated Deployment
    • Building Data Repositories
  • Organising Your Data (Model)
    • How to Organise Your Data
    • URI Design
    • Versioning
    • Metadata
      • Group
      • Artifact
      • Version
      • Distribution
      • Collection
    • Content Variants
    • Persistence (HowTo)
  • Usage
    • Quickstart Examples (Publish, Download)
    • Web Interface
      • Publish
      • Collections
      • Auto-Completion
    • API
    • Databus Mods
    • Databus Client
    • Integration with CI (Jenkins)
  • Running Your Own Databus Server
    • Run with Docker
    • Configuration
    • HTTPS & Proxy Setup
  • Development Environment
Powered by GitBook
On this page

Organising Your Data (Model)

One of the distinguishing features of Databus technology lies in its unique approach to data organization. To make the most of this powerful tool, it is crucial to understand and adopt the Databus data model. This section provides a detailed overview of the Databus data model, covering key concepts such as URI design, versioning, metadata (group, artifact, version, distribution), and content variants. Through the use of examples and best practices, you will gain a comprehensive understanding of how to efficiently utilize the Databus data model. By delving into this comprehensive overview, you'll be empowered to unlock the full potential of the Databus and effectively manage your data. Let's embark on a journey into the world of the Databus data model together.

PreviousBuilding Data RepositoriesNextHow to Organise Your Data

Last updated 2 years ago