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Welcome to the trace-registry! This project helps manage a lot of information in a structured and traceable way. Think of it like a big, smart digital library. In this first chapter, we'll explore the very foundation of how this library organizes its contents: Catalogue and Dataset Management.

What's the Big Idea? Organizing Our Digital Library

Imagine you're building a massive online library for environmental information. You'll have information about:

  • Different energy projects (solar, wind, etc.)
  • Standards for forestry and agriculture
  • Methodologies for calculating carbon footprints
  • Supporting documents, reports, and data files

If all this information was just thrown into one giant pile, it would be impossible to find anything! This is where "Catalogue & Dataset Management" comes in. It's the system that acts like a librarian, organizing everything neatly so it's easy to find, understand, and use.

Our main goal is to:

  1. Organize diverse information into logical collections.
  2. Describe each piece of information in a standard way.
  3. Make it easy to discover and access what you need.

Let's break down the key concepts that make this happen.

Key Concepts: The Building Blocks

1. Catalogues: The Main Sections

Think of Catalogues as the main sections or top-level bookshelves in our digital library.

  • Examples: 'Renewable Energy Projects', 'Forestry Carbon Standards', 'Approved Methodologies'.
  • Hierarchical: Catalogues can also contain other, more specific catalogues. For instance, 'Renewable Energy Projects' might have sub-catalogues like 'Solar Projects' and 'Wind Projects'. This creates a tree-like structure, making it easy to navigate from general topics to specific ones.

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DCat API is built using the Fixers framework and is based on Neo4j.

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