ontodag 0.1.0

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) and future plans.
• 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

• Implement the basic DAG data structure (put, remove)
• Simplify definitions not to include unnecessary links (e.g. bird under animal, animal is not needed)
  • During put keep a dictionary of 'done' nodes of the inserted item and all its super categories
  • Insert a link only to nodes which are not 'done'
  • Increment counter only for items which are not 'done'
• Save/load data structure into/from file (try PKL)
• Load ontology from file (e.g. OWL)
• Visualize graph (with python library - Graphviz)
• More extensive test cases
• Select suitable ontology for importing (to serve as the basis of the DAG)
• Sub-class of OntoDAG with counters (for statistics)
• Predicated (parametric) items. Dealing with items not stored in the graph (e.g. numbers, intervals, geo coordinates, areas; general, hierarchical types (types stored in the graph))
• Implement space and time calculation for graph items (e.g. century, GPS bounding box)
  • categories for item types, e.g. point in time, time interval, geo coordinates, geo area, url
  • way to handle non-stored numerical types (time intervals, geo coordinates, areas, numbers, arbitrary types)
  • way to store and retrieve ordered values (photo with exact time in response to "last week")
  • ways to define (partial) ordering function
  • file types (hierarchical, e.g. image, png)
• Name usage across different instances of OntoDAG:
  • namespaces
  • avoiding confusing names (different language and usage, spelling)
  • ability to merge DAGs with different name usage, using namespaces
• Optimize retrieval and storage by choosing subsets of query items and finding existing nodes already stored in the DAG.
• Add and remove intermediate nodes to optimize search in the graph
• Port implementation to Golang
• Implement a REST API for the Golang (or Rust) implementation
• Interface with a graph database implementation.
• Implement a web interface for the REST API & host it on a website with user profiles
• Implement a limited functionality (DAG-only) graph database for Ethereum Swarm
• Design a plugin for Ethereum Swarm to store the DAG in a decentralized way

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