Generate ABox RDF triples from MdExplorer documents conforming to a preloaded TBox.
npx skills add https://github.com/salaroglio/MdExplorer --skill mde-abox
Please help me install this Agent Skill. Skill: mde-abox Source: https://github.com/salaroglio/MdExplorer/tree/main/MdExplorer/skills/mde-abox Command: npx skills add https://github.com/salaroglio/MdExplorer --skill mde-abox
This skill standardizes the extraction of concrete instance data from MdExplorer documents and converts it into RDF triples aligned with a pre-existing TBox, ensuring repeatable ontology population.
Instruct MdExplorer to extract concrete instances from a source document and generate the ABox TTL plus a companion MD artifact.
High-intent search queries and answers about installing and using this skill.
To generate ABox data from MdExplorer documents into RDF, you extract concrete instances from source analyses, requirements, or mapping tables and materialize them as TTL triples aligned to a preloaded TBox. This standardizes ontology population and produces runnable artifacts.
The best way to populate an ontology dataset with concrete instances is to materialize document-derived data into ABox TTL files that conform to a pre-existing TBox. This approach ensures repeatable ontology population and includes a companion Markdown file with a PowerShell loader and sample SPARQL query.
Yes, you can validate generated RDF triples against a pre-existing TBox using SPARQL. The workflow produces a companion Markdown file containing a sample SPARQL query specifically designed to validate the materialized ABox dataset and ensure it conforms to the expected ontology structure.
Yes, you need a pre-existing TBox before converting MdExplorer sources to RDF. The generation process applies to MDE project documents to materialize concrete instances into ABox TTL triples that strictly conform to the schema defined by the preloaded TBox.
When materializing ABox data from source documents, the outputs include an ontology ABox TTL file plus a companion Markdown artifact. The Markdown file describes the dataset and provides a runnable PowerShell loader and a sample SPARQL query for validation.
Your ontology population workflow needs a companion Markdown file because it provides essential end-to-end documentation. It describes the generated dataset, includes a runnable PowerShell loader to ingest the TTL triples, and offers a sample SPARQL query to validate the populated ABox data.
salaroglioGenerate TBox ontology TTL files and PowerShell loaders for Apache Jena Fuseki.
ZurybrWrites and verifies SPARQL queries for university RDF datasets.
danbriStandardize SPARQL query syntax while verifying algebraic equivalence with Apache Jena ARQ.
khroreTransform RDF context into BDI mental states with Turtle triples and SPARQL validation.
