Marble Releases Open Elementary Curriculum Taxonomy Dataset with 1,861 Micro-Topics
· GlobeWire Daily Editorial Desk · Source: github.com

Image: GitHub · Photo source · Resized and letterboxed to 16:9; no AI generation
Marble has released an open, structured taxonomy mapping elementary school learning into fine-grained micro-topics, prerequisite graphs, and national curriculum standards. Designated as version v1, the dataset provides a connected graph of learning designed to show how educational concepts interlink across primary education.
Dataset Structure and Scope
The public release organizes elementary education data into machine-readable UTF-8 JSON files containing:
- 1,861 micro-topics, each representing a single teachable idea equipped with a plain-language description, mastery criteria, classification type, and age range.
- 4,003 prerequisite dependencies, forming a directed acyclic graph where each edge indicates a directional prerequisite relationship labeled as hard or soft.
- Curriculum alignment records, linking micro-topics to established frameworks such as the Next Generation Science Standards (NGSS), Common Core, and the UK National Curriculum.
- 1,049 teaching-research records, providing pedagogical guidance and activity proposals linked to specific concepts.
Jurisdictional Integrations and Reviews
The repository details extensive alignment work across international standards, including updates for the Australian Curriculum, Ontario elementary expectations, and draft NCERT foundational frameworks. Grade-by-grade reviews for Ontario mathematics and science document how local standards map onto the core taxonomy without certifying individual student mastery.
Practical Implications and Verification
- Pure Data Architecture: The repository operates as a static data collection requiring no proprietary runtime or background dependencies.
- Licensing: The database is distributed under the Open Database License (ODbL 1.0), while text and content fall under Creative Commons Attribution-ShareAlike (CC BY-SA 4.0).
- Verification: Users can inspect schemas, verify SHA-256 manifest checksums, and run validation scripts using standard Node.js commands (`npm test` and `npm run validate`) directly from the public GitHub repository.
AI-assisted reporting; source claims are attributed and have not been independently verified.
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