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Ontologies that aim to provide semantic specifications for units of measure, quantity kind, dimensions and data types.

Identifiers in the GTN correspond to training materials in various formats (markdown, slides, video). The users can apply learned concepts directly within the framework via galaxy workflows.

Bioschemas aims to improve the Findability on the Web of life sciences resources such as datasets, software, and training materials. It does this by encouraging people in the life sciences to use Schema.org markup in their websites so that they are indexable by search engines and other services. Bioschemas encourages the consistent use of markup to ease the consumption of the contained markup across many sites. This structured information then makes it easier to discover, collate, and analyse distributed resources. [from BioSchemas.org]

The Bioregistry is integrative meta-registry of biological databases, ontologies, and nomenclatures that is backed by an open database.

A representation of variables appearing in models in the environmental research space.

A vocabulary for describing semantic assets, defined as highly reusable metadata (e.g. XML1 schemata, generic data models) and reference data (e.g. code lists, taxonomies, dictionaries, vocabularies).

BioTools is a registry of databases and software with tools, services, and workflows for biological and biomedical research.

An Apache-based persistent URL (PURL) service

An international LGBTQ+ linked data vocabulary

The Generative Artificial Intelligence Delegation Taxonomy (GAIDeT) assigns identifiers to contributor roles as an extension to the Contributor Roles Taxonomy (CRediT) to support promoting transparency and accountability in academic publishing when AI contribtors are involved in research. It is operationalized in the [GAIDeT Declaration Generator](https://panbibliotekar.github.io/gaidet-declaration/), an interactive tool for researchers to disclose the delegation of tasks to generative AI (GAI) tools in accordance with the GAIDeT taxonomy.

CCSO is an educational ontology acting as a data model for concepts and entities within an academic setting, enabling also the annotation of potentially available resources. The ontology aims to conceptualize educational entities within Curriculum and Syllabus with appropriate coverage and quality, in order to support rich services on top for improving curriculum management and automatically enabling syllabus semantic processes. (from homepage)

HOSO is an ontology of informational entities and processes related to healthcare organizations and services.

An ontology of information entities about an individual

Unified Code for Units of Measure (UCUM) is a code system intended to include all units of measures being contemporarily used in international science, engineering, and business.

A concept scheme that defines the types of relationships between a learning resource and a node in an educational framework.

BioCompute is shorthand for the IEEE 2791-2020 standard for Bioinformatics Analyses Generated by High-Throughput Sequencing (HTS) to facilitate communication. This pipeline documentation approach has been adopted by a few FDA centers. The goal is to ease the communication burdens between research centers, organizations, and industries. This web portal allows users to build a BioCompute Objects through the interface in a human and machine readable format.

TogoID is an ID conversion service implementing unique features with an intuitive web interface and an API for programmatic access. TogoID supports datasets from various biological categories such as gene, protein, chemical compound, pathway, disease, etc. TogoID users can perform exploratory multistep conversions to find a path among IDs. To guide the interpretation of biological meanings in the conversions, we crafted an ontology that defines the semantics of the dataset relations. (from https://togoid.dbcls.jp/)

The Shape Expressions (ShEx) language describes RDF nodes and graph structures. A node constraint describes an RDF node (IRI, blank node or literal) and a shape describes the triples involving nodes in an RDF graph. These descriptions identify predicates and their associated cardinalities and datatypes. ShEx shapes can be used to communicate data structures associated with some process or interface, generate or validate data, or drive user interfaces.