ontology-mapper

Ontology Mapper

Goal

Translate real-world materials science descriptions into standardized ontology annotations. Given terms like "FCC copper" or structured data like {"material": "iron", "structure": "BCC", "lattice_a": 2.87}, produce the corresponding ontology classes and properties for any registered ontology.

Requirements

• Python 3.10+
• No external dependencies (Python standard library only)
• Requires ontology-explorer's summary JSON and ontology_registry.json
• Per-ontology mapping config (<name>_mappings.json) for ontology-specific synonyms and labels

Inputs to Gather

Decision Guidance

What do you need to map?
├── A concept or term to find its ontology class
│   └── concept_mapper.py --ontology <name> --term "<term>"
├── Crystal structure parameters to ontology terms
│   └── crystal_mapper.py --ontology <name> --bravais <type> --space-group <N> --a <val>
├── A full sample description to ontology annotations
│   └── sample_annotator.py --ontology <name> --sample '<json>'
└── Multiple terms at once
    └── concept_mapper.py --ontology <name> --terms "term1,term2,term3"

Ontology scope — crystal/sample annotation is CMSO-only. crystal_mapper.py and sample_annotator.py emit crystal-structure vocabulary (Crystalline Material, Crystal Structure, Unit Cell, Space Group, lattice properties). This vocabulary is defined by CMSO. ASMO is a simulation-methods ontology and does not define any crystal/sample classes — so for ASMO use the concept-mapping path (concept_mapper.py, which resolves terms like DFT, NPT, timestep, PBE to real ASMO classes) only. If sample_annotator.py/crystal_mapper.py is run with an ontology whose summary lacks the required classes (e.g. --ontology asmo), each unresolvable term is flagged in results.validation_warnings and given confidence: 0.0 rather than silently emitting an invalid term.