ontodag 0.3.0

Associative memory and categories based on a directed acyclic graph data structure

OntoDAG

Associative memory and categories based on a directed acyclic graph data structure

Documentation

• User Guide — installation, tutorial, Python API, command line, web app/REST, file formats, troubleshooting. Start here.
• How It Works Inside — the design in plain language (canonical form, query planning, content-addressed persistence).
• Roadmap — delivered, queued, parked, and research horizon.
• docs/SWARM_DESIGN.md, docs/SEMANTIC_CODES.md — engineering design documents.

See also ontodag-fs: any OntoDAG store can be browsed as a filesystem — paths are category queries, files are classified objects stored on Swarm, FUSE-mountable (odag-fs, which shares odag's store settings).

Specification

A Directed Acyclic Graph (DAG) associative storage and category manager in Python. You can store items into a ontodag and recall items from it. To store or "put" an item into a ontodag, you give it a name and a set of other names of already existing items that are its supercategories. To recall or "get", you specify a set of item names to get all items that are subcategories of all these items.

Roadmap

The roadmap — what is done, what is queued next, what is parked and why — is in docs/ROADMAP.md. Longer-term goals for the database direction (and the features deliberately not built yet) are in docs/DATABASE_DIRECTION.md; the day-to-day task list is in CLAUDE.md.

Potential Applications

• Using the ontology graph for content categorization instead of folders
• Replace content tags with a more structured ontology
• Access control (ACT) groups
• Memberships in organizations and gate content based on membership
• Communication channel groups defined by the ontology
• Fostering deals within a universal marketplace for services and goods