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infer-ontology

Infer a semantic ontology from files and output ONTOLOGY.md.

3.7k|104|Updated Dec 11, 2020
Search Tags:#ontology#metadata#data-modeling#taxonomy#data-profiling#cross-file#data-discovery
One-click install
npx skills add https://github.com/dathere/qsv --skill infer-ontology
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: infer-ontology
Source: https://github.com/dathere/qsv/tree/main/.claude/skills/skills/infer-ontology
Command: npx skills add https://github.com/dathere/qsv --skill infer-ontology

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Infer semantic ontology from all files in the working directory, identifying entities, attributes, relationships, domain taxonomy, and cross-file join paths. Outputs ONTOLOGY.md.

Core Features & Use Cases

  • Profile tabular and non-tabular files to extract entities, attributes, relationships, and synthesize a unified ontology.
  • Generate ONTOLOGY.md with an entity-relationship view, domain taxonomy, and metadata tags for governance and discovery.
  • Use case: map a collection of CSVs, JSON, and text files into a coherent schema to enable semantic querying and data governance.

Quick Start

Run the ontology inference in the current directory to create ONTOLOGY.md.

Frequently Asked Questions about infer-ontology

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I infer a semantic ontology from a collection of CSV and JSON files?▼

To infer a semantic ontology from multiple files, this Skill profiles all tabular and non-tabular data in your working directory to identify entities, attributes, relationships, and cross-file join paths, outputting an ONTOLOGY.md document.

What is the best way to map cross-file join paths and domain taxonomy across unstructured data?▼

Mapping cross-file join paths and domain taxonomy is achieved by profiling all files in the working directory to extract data dictionaries and synthesize a unified ontology, targeting both tabular and non-tabular sources.

Can I generate an entity-relationship model and data dictionary without manual data profiling?▼

Generating an entity-relationship model and data dictionary is fully automated; the Skill profiles your files to extract entities, attributes, keys, and relationships, then outputs the complete metadata structure into ONTOLOGY.md.

Does ontology inference work with non-tabular data formats like text files?▼

Ontology inference works with both tabular and non-tabular data sources, profiling various file formats to map domains, extract metadata tags, and synthesize a coherent schema for semantic querying.

How do I extract data governance metadata from a directory of mixed file types?▼

Extracting data governance metadata involves profiling mixed file types to map domain taxonomy, identify cross-file links, and generate an ONTOLOGY.md file with metadata tags designed for data discovery and governance.

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