Execute qualquer Skill no Manus
com um clique

Execute qualquer Skill no Manus com um clique

ontology-map

Estrelas2

Forks0

Atualizado6 de fevereiro de 2026 às 23:03

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

Instalação

Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.

Executar no Manus

Fonte

dandye

dandye/information-architecture

Abrir repositório GitHub Ver repositórios do creator

Download

Executar no Manus

Ocupações relacionadasSOC

Baseado na classificação ocupacional SOC

Desenvolvedores de softwareInformática e Matemática·SOC 15-1252

Explorador de arquivos

2 arquivos

SKILL.md

readonly

name	ontology-map
description	Map local tags, categories, or terms to standard formal ontologies (like SKOS or industry-specific standards) to ensure interoperability.
required_roles	{"scribe":"roles/scribe.editor"}
personas	["taxonomist","information-architect"]

Ontology Mapper Skill

Analyze a list of local terms (tags, categories) and suggest mappings to standard ontologies to improve content classification and interoperability.

Inputs

SOURCE_TERMS - A list of terms or a path to a file containing terms to map.
TARGET_ONTOLOGY - (Optional) The standard ontology to map to (e.g., "SKOS", "Dublin Core", "Schema.org"). Default: "SKOS".

Workflow

Analyze: Review the SOURCE_TERMS to understand their local context and usage.
Search: Look up potential matches in the TARGET_ONTOLOGY spec.
Map: suggest:
- Exact Match (skos:exactMatch)
- Broader Match (skos:broader)
- Narrower Match (skos:narrower)
- Related Match (skos:related)

Output

A mapping table (Markdown or CSV) linking Input Term -> Target URI/Term -> Relation Type.

Mais deste repositório

mesmo repositório

named-entity-normalization

dandye/information-architecture

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

2026-05-232

vocabulary-overlap-analysis

dandye/information-architecture

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

2026-05-232

document-tree-generate

dandye/information-architecture

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

2026-04-092

ontology-define

dandye/information-architecture

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

2026-02-062

content-inventory

dandye/information-architecture

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

2026-02-062

json-ld-generate

dandye/information-architecture

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

2026-02-062

name	ontology-map
description	Map local tags, categories, or terms to standard formal ontologies (like SKOS or industry-specific standards) to ensure interoperability.
required_roles	{"scribe":"roles/scribe.editor"}
personas	["taxonomist","information-architect"]

Ontology Mapper Skill

Analyze a list of local terms (tags, categories) and suggest mappings to standard ontologies to improve content classification and interoperability.

Inputs

SOURCE_TERMS - A list of terms or a path to a file containing terms to map.
TARGET_ONTOLOGY - (Optional) The standard ontology to map to (e.g., "SKOS", "Dublin Core", "Schema.org"). Default: "SKOS".

Workflow

Analyze: Review the SOURCE_TERMS to understand their local context and usage.
Search: Look up potential matches in the TARGET_ONTOLOGY spec.
Map: suggest:
- Exact Match (skos:exactMatch)
- Broader Match (skos:broader)
- Narrower Match (skos:narrower)
- Related Match (skos:related)

Output

A mapping table (Markdown or CSV) linking Input Term -> Target URI/Term -> Relation Type.