This repo+wiki presents a mid-level ontology for linked data within the ADRF framework use cases, based on SKOS. Note that "Turtle" format is used for what people need to read and understand, while JSON-LD format is used for the data that machines need to process.

Overall, Rich Context provides the knowledge graph work associated with ADRF, which gets used for:

• data catalog, dataset curation, and data governance in ADRF
• recommendations for analysts (e.g., meta-learning)
• estimating the impact of datasets for evidence-based policymaking and the US federal data strategy
• reference implementation for the JupyterLab Metadata Service
• controlled vocabulary for the public corpus used in the RCLC leaderboard competition

The general category for metadata management and other related practices is defined by the FAIR Data Principles provide "guidelines to improve the findability, accessibility, interoperability, and reuse of digital assets":

• "The FAIR Guiding Principles for scientific data management and stewardship"

Implementing the FAIR principles, the following controlled vocabularies get used (referenced, extended) to describe metadata for datasets and data catalog, along with the research publications and researchers involved:

• DCAT
• VoID
• PAV
• FaBiO
• CITO
• FOAF
• DCMI
• MADS/RDF

At its core, the Rich Context knowledge graph is a DCAT-compliant data catalog, then optionally the individual entities may leverage a set of upper ontologies:

• NIH Mesh vocabulary
• Global Change Master Directory keywords
• SAGE Social Science Thesaurus vocabulary
• Library of Congress subject headings and authorities
• Wikidata
• DBpedia resources

See the Vocabulary page for detailed listings of our local entities -- and our TODO list.

• "Rich Context in the Administrative Data Research Facility"
• "Knowledge Graphs"
• Semantic Modeling for Data
• "Dataset Catalogs as a Foundation for FAIR Data"
• "W3C: Complete Example of a Dataset Description"
• "Understanding Linked Data Formats"
• "Making Sense of Linked Data with Python"
• "Literature of Deep Learning for Graphs"
• "A Standard to build Knowledge Graphs: 12 Facts about SKOS"
• "Inspecting an ontology with RDFLib"

• richcontext.scholapi
• EasyRDF Converter
• Google Dataset Search
• PoolParty