information-architecture

Normalize named entities and concept variants into canonical forms using controlled vocabularies or standard taxonomies.

Analyze vocabulary overlap and identify named entities unique to domain/document corpora.

Transform lengthy documents into a semantic tree structure. It extracts sections, summaries, and hierarchies optimized for use with Large Language Models (LLMs).

Design formal ontologies using OWL/RDFS. Defines classes, properties, and relationships for complex semantic modeling.

Systematic cataloging of information assets. Creates comprehensive inventories or card sorting materials from content.

Generate JSON-LD structured data for web content. Maps content to Schema.org types to improve search engine understanding and rich result eligibility.

Analyze multiple documents to extract entities and relationships, generating a knowledge graph structure (RDF/Turtle).

Map local tags, categories, or terms to standard formal ontologies (like SKOS or industry-specific standards) to ensure interoperability.

Extract structured data and entities from existing HTML, Markdown, or text files to audit metadata availability.

Validate existing JSON-LD or Microdata in documents against Schema.org standards to ensure correctness and search engine readability.

Generate materials for card sorting studies. Creates detailed lists of content items (cards) for user research and information architecture validation.

Visualize user paths and interactions. Creates flowcharts representing user journeys to complete specific tasks.

Generate semantic web markup (JSON-LD, Schema.org) for documents. Enhances SEO and machine readability by extracting entities and structural data.

Identify content gaps and organizational opportunities. Analyzes missing content areas, redundancies, and consolidation opportunities.

Comprehensive content quality and maintenance assessment. Evaluates documentation quality, relevance, maintenance needs, and provides actionable recommendations.

Design comprehensive metadata frameworks. Develops structured metadata templates and tagging systems.

Generate hierarchical site structure and navigation maps. Creates visual representations of information architecture and content relationships.

Develop hierarchical classification systems. Creates parent-child categorical structures for content organization.

Generate controlled vocabulary thesaurus for content domains. Creates comprehensive thesauri with preferred terms, broader/narrower/related terms.