Concept relationships
Map broader, narrower, equivalent, related, conflicting, historical, and deprecated concepts.
Feature
Your domain ontology
Model the concepts, relationships, constraints, and hierarchies that make your field difficult to translate.
A knowledge model for your language work.
Every domain has structure: roles, institutions, objects, processes, categories, exceptions, and inherited meanings. A domain ontology makes that structure explicit so terms are translated through relationships, not only dictionary entries.
Idanium connects ontology records to terminology, examples, source evidence, translation memory, guardrails, search, and workflow decisions.
Domain constraints
Capture which terms apply by jurisdiction, period, institution, audience, or register.
Source grounding
Link concepts to sources, examples, citations, dates, and evidence quality.
Customer specificity
Model the customer's actual field, not a generic public taxonomy.
What this adds
The ontology gives the platform its memory of meaning.
A glossary says what word to use. An ontology explains what the word belongs to and when that choice is valid.
Search
Find related concepts even when wording differs across languages, scripts, or departments.
Quality
Detect when a translation uses a near concept that is not actually equivalent.
Governance
Attach ownership, approval, source authority, and review requirements to concept families.
Connected records
Ontology records connect structure to daily workflow.
The ontology is practical: it helps people search, translate, review, simplify, and maintain language over time.
Hierarchies
Parent concepts, child concepts, subtypes, and part-whole relationships.
Constraints
Jurisdiction, period, document type, audience, institution, region, and register.
Evidence
Source documents, examples, citations, review notes, and confidence levels.
Downstream links
Glossary terms, memory segments, guardrails, tasks, and notifications.