[FEATURE] Dedicated SKOS Vocabulary Module (Using Existing Components)

[KaifAhmad1]

Manage controlled vocabularies, taxonomies, and term relationships on top of Semantica’s existing ontology and triplet‑store stack.

No new Python package is added; we extend the current ontology and RDF infrastructure.

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Code and Test Layout

• Main implementation goes in existing packages:
  • semantica/ontology/ (for public APIs and namespace handling).
  • semantica/triplet_store/ (for RDF storage and SPARQL).
• Tests for SKOS features should be added under:
  • tests/ontology/ (ontology‑level helpers).
  • tests/triplet_store/ (triple store behavior).
• Do not create new top-level folders; reuse semantica/ and tests/ only.

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Feature Description

• Stores SKOS concept schemes, concepts, and collections in the existing RDF store.
• Provides search, browse, and selection for SKOS concepts.
• Uses SKOS vocabularies to drive suggestions, autocomplete, and validation.
• Integrates with ontology and graph workflows as a first‑class semantic asset.

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Why This Is Important

• Improves semantic search accuracy and term matching.
• Centralizes enterprise vocabularies and taxonomies.
• Reduces ambiguity and drift in labels and domain terminology.
• Moves Semantica toward being a complete semantic layer platform, not just a graph toolkit.

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Existing Building Blocks

These are existing modules and files in Semantica that SKOS support will build on:

• Ontology and namespaces
  • semantica/ontology/namespace_manager.py
    • Manages prefixes and base URIs (OWL, RDF, etc.).
  • semantica/ontology/module_manager.py
    • Handles modular ontologies and imports.
  • semantica/ontology/engine.py
    • High‑level ontology API (generation, validation, export).
• Triplet store and SPARQL
  • semantica/triplet_store/triplet_store.py
    • Generic RDF triple storage operations.
  • semantica/triplet_store/query_engine.py
    • SPARQL execution and optimization.
  • semantica/triplet_store/config.py
    • Configuration for triplet store backends.
• Documentation and tests
  • docs/reference/ontology.md
  • docs/reference/triplet_store.md
  • tests/ontology/test_ontology_comprehensive.py
  • tests/triplet_store/test_triplet_store.py

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New Work on Top of Existing Code

All work should extend the files above; no new top‑level modules are required:

• Add SKOS namespace support
  • In semantica/ontology/namespace_manager.py:
    • Ensure SKOS prefix and base URI are defined.
    • Optionally add helpers for building SKOS URIs.
• Add lightweight SKOS helpers on top of the triplet store
  • In semantica/triplet_store/triplet_store.py:
    • Optional helper methods for adding and retrieving SKOS concepts using existing triple APIs.
• Add ontology‑level vocabulary APIs
  • In semantica/ontology/engine.py (or a small helper in the same package):
    • New public methods:
      • list_vocabularies()
      • list_concepts(scheme_uri: str)
      • search_concepts(query: str, scheme_uri: Optional[str] = None)
    • These should delegate to QueryEngine from semantica/triplet_store/query_engine.py.
• Add docs and tests
  • docs/reference/ontology.md:
    • New “SKOS Vocabulary Management” section with usage examples.
  • tests/ontology/test_ontology_comprehensive.py:
    • Tests for ontology‑level SKOS helpers.
  • tests/triplet_store/test_triplet_store.py:
    • Tests that SKOS triples can be stored and retrieved correctly.

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Implementation Plan

1. SKOS namespace support

   • In ontology/namespace_manager.py:
     • Ensure SKOS prefix and base URI are defined (e.g. http://www.w3.org/2004/02/skos/core#).
     • Provide convenience helpers to construct SKOS URIs where useful.

2. RDF storage of SKOS vocabularies

   • In triplet_store/triplet_store.py:
     • Confirm that storing SKOS triples requires no backend changes.
     • If needed, add small helper methods such as:
       • add_skos_concept(...)
       • get_skos_concepts(...)
     • Internally these should just call the generic triple APIs.

3. Search and retrieval helpers

   • In ontology/engine.py (or a small helper within the ontology package):
     • Implement public methods:
       • list_vocabularies()
       • list_concepts(scheme_uri: str)
       • search_concepts(query: str, scheme_uri: Optional[str] = None)
     • Use triplet_store/query_engine.QueryEngine to issue SPARQL SELECT queries over the RDF store, matching labels, altLabels, and notations.

4. Integration points

   • Keep this feature opt‑in and non‑breaking:
     • When SKOS vocabularies exist, they can be used by other modules (e.g. semantic extraction, KG, mapping) via public ontology APIs.
   • Do not introduce new modules; feed everything through existing ontology and triplet_store entrypoints.

5. Documentation

   • In docs/reference/ontology.md:
     • Add a “SKOS Vocabulary Management” section with examples:
       • Importing a SKOS vocabulary via existing RDF import tools.
       • Listing and searching concepts through OntologyEngine.
   • Optionally cross‑link from docs/reference/triplet_store.md.

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When This Feature Is Considered Complete

• SKOS vocabularies (schemes, concepts, collections) can be:
  • Imported into the existing RDF store.
  • Listed and searched using ontology APIs that wrap QueryEngine.
• No new top‑level Python package is created.
• Tests cover:
  • Basic SKOS vocabulary ingestion and retrieval.
  • At least one search scenario (e.g. prefLabel + altLabel matching).
• Documentation explains how contributors and users can work with SKOS vocabularies in Semantica.