dandye/information-architecture

named-entity-normalization

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

Quellsprache: Englisch

vocabulary-overlap-analysis

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

Quellsprache: Englisch

document-tree-generate

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

Quellsprache: Englisch

ontology-define

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

Quellsprache: Englisch

content-inventory

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

Quellsprache: Englisch

json-ld-generate

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

Quellsprache: Englisch

knowledge-graph-generate

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

Quellsprache: Englisch

ontology-map

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

Quellsprache: Englisch

semantic-extract

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

Quellsprache: Englisch

semantic-validate

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

Quellsprache: Englisch

card-sorting-generate

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

Quellsprache: Englisch

user-flow-generate

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

Quellsprache: Englisch

semantic-markup-generate

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

Quellsprache: Englisch

content-analyze-gaps

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

Quellsprache: Englisch

content-audit

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

Quellsprache: Englisch

metadata-schema-design

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

Quellsprache: Englisch

sitemap-generate

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

Quellsprache: Englisch

taxonomy-generate

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

Quellsprache: Englisch

thesaurus-generate

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

Quellsprache: Englisch