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A data model for managing information about chemical entities, ranging from atoms through molecules to complex mixtures.

The Common Core Ontologies (CCO) comprise twelve ontologies that are designed to represent and integrate taxonomies of generic classes and relations across all domains of interest. CCO is a mid-level extension of Basic Formal Ontology (BFO), an upper-level ontology framework widely used to structure and integrate ontologies in the biomedical domain (Arp, et al., 2015). BFO aims to represent the most generic categories of entity and the most generic types of relations that hold between them, by defining a small number of classes and relations. CCO then extends from BFO in the sense that every class in CCO is asserted to be a subclass of some class in BFO, and that CCO adopts the generic relations defined in BFO (e.g., has_part) (Smith and Grenon, 2004). Accordingly, CCO classes and relations are heavily constrained by the BFO framework, from which it inherits much of its basic semantic relationships.

The System Package Data Exchange™ (SPDX®) specification is an open standard designed to represent systems containing software components as Software Bill of Materials (SBOMs). Additionally, SPDX supports AI, data, and security references, making it suitable for a wide range of risk management use cases. This _spdx3_ prefix is for SPDX 3.x versions. For earlier versions, use _spdx.term_.

EMMO is a multidisciplinary effort to develop a standard representational framework (the ontology) for applied sciences. It is based on physics, analytical philosophy and information and communication technologies. It has been instigated by materials science to provide a framework for knowledge capture that is consistent with scientific principles and methodologies. (from GitHub)

OEO is a domain reference ontology for energy system modeling.

The information resource registry is a listing of data sources present in the NCATS Data Translator system. Each information resource has an identifier, a short description, and a URL to more information about that resource.

The DCAT-AP conversion to a LinkML Schema is the intended point of truth for the DCAT-AP+ schema, but could be used alternatively as a LinkML representation of DCAT-AP for other Projects. It is a port of DCAT-AP to the LinkML world that is as faithful to the original as possible. This Persistent Identifier does not only provide the SHACL Shape, but could also be used as described [here](https://github.com/perma-id/w3id.org/tree/cecbc2e5f40d928f05ed5306d24fc60db0e7bb21/nfdi-de/dcat-ap-plus). DCAT-AP+ is a [LinkML](https://linkml.io/)-based extension of the [DCAT Application Profile 3.0](https://semiceu.github.io/DCAT-AP/releases/3.0.0/) that adds a provenance layer for describing how a dataset was generated and what it is about, using the [Starting Point Terms of PROV-O](https://www.w3.org/TR/prov-o/#description-starting-point-terms), the [QUDT ontology](https://www.qudt.org/), and [Dublin Core Terms](http://purl.org/dc/terms/).

Some IDs may represent experiment sets, e.g. https://www.mavedb.org/#/experiment-sets/urn:mavedb:00000011 Others represent genomic regions (specifically deep mutational scans thereof) e.g. https://www.mavedb.org/#/experiment-sets/urn:mavedb:00000011-a

Ontology representation of the [International Committee on Taxonomy of Viruses (ICTV)](https://ictv.global/) for the [EVORA project](https://evora-project.eu/)

A classification of subjects in Hochschule (universities of applied sciences)

Terms for genes, experimental factors, and cell lines used by the [Gemma platform](https://gemma.msl.ubc.ca/home.html) for differential gene expression analysis.

MITE (Minimum Information about a Tailoring Enzyme) is a data repository and associated data standard designed to capture the reaction- and substrate-specificities of tailoring enzymes. Community-driven and fully expert-reviewed, it represents enzymatic reactions using reaction SMARTS and links to established resources such as UniProt, NCBI GenPept, Rhea, and MIBiG. MITE serves as a knowledgebase for enzyme and pathway annotation, in silico biosynthesis, and machine learning applications.

METPO (Microbial Ecophysiological Trait and Phenotype Ontology) provides standardized terms for describing microbial phenotypes, growth characteristics, and culture conditions. It includes classes for growth media, temperature tolerances, pH tolerances, and relationships like "grows in" and "does not grow in".

SSSOM is a Simple Standard for Sharing Ontological Mappings, providing - a TSV-based representation for ontology term mappings - a comprehensive set of standard metadata elements to describe mappings and - a standard translation between the TSV and the Web Ontology Language (OWL). Most metadata elements, such as "sssom:mapping_justification" are defined in the sssom namespace.

The Ontology of Immune Epitopes (ONTIE) is an effort to represent terms in the immunology domain in a formal ontology with the specific goal of representing experiments that identify and characterize immune epitopes.

The Chromosome Ontology is an automatically derived ontology of chromosomes and chromosome parts.

The Simplified Upper Level Ontology (SULO) is ontology with a minimal set of classes and relations to guide the development of a personal health knowledge graph. [from homepage]

The HGVS Nomenclature is an internationally-recognized standard for the description of DNA, RNA and protein sequence variants. It is used to convey variants in clinical reports and to share variants in publications and databases. The HGVS Nomenclature is administered by the [HGVS Variant Nomenclature Committee (HVNC)](https://hgvs-nomenclature.org/stable/hvnc/) under the auspices of the [Human Genome Organization (HUGO)](https://hugo-int.org/).

The EVORAO Ontology provides a structured and harmonized vocabulary for describing shareable pathogens as characterized biological materials, along with their derived products and associated services, organized into collections. Developed within the EVORA project, it supports consistent metadata annotation across research infrastructures, promoting findability, accessibility, interoperability, and reusability (FAIR). By aligning with relevant standards and ontologies, EVORAO facilitates cross-domain collaboration, integration, and sharing of pathogenic resources and services to enhance pandemic preparedness and response. While initially focused on virology, EVORAO is designed to be extensible and also supports metadata harmonization for other pathogens. [from repository]

The submission-centric metadata schema for the German Human Genome-Phenome Archive (GHGA).

An extension of Schema.org to annotate metadata on software projects

The EMI ontology is used to structure spectrum annotation provenance by reusing the PROV-O ontology (a W3C recommendation) and sample and observation data by applying the SOSA ontology. EMI reuses the SOSA ontology as a data schema for struturing the Sample and Observation data. SOSA (Sensor, Observation, Sample, and Actuator) is a subset of SSN (Semantic Sensor Network Ontology) that is a W3C recommendation. [from homepage]

The Context and Measurement Ontology (COMO) contains ontological terms to describe the context for various types of experimental data and measurements. It is useful in its current state for several different environmental microbiology projects. This ontology is used in multiple CORAL (Contextual Ontology-based Repository Analysis Library) deployments.

An EMMO-based domain ontology for atomistic and electronic modelling.

The Graphic Descriptor Ontology (GDO) is intended for use in describing graphics that represent the form of objects. It uses the language of visual communication, illustration, and technical drawing. The GDO is rooted in the Basic Formal Ontology (BFO) and uses several classes from the Information Entity Ontology of the Common Core Ontologies as a mid-level ontology. [from https://gdo.endlessforms.info/about]

This ontology integrates cell type markers for cells in the Cell Ontology from various sources along with details of marker context (anatomical context, assay), confidence (where available) and provenance. [from repository]

The Bibframe vocabulary consists of RDF classes and properties used for the description of items cataloged principally by libraries, but may also be used to describe items cataloged by museums and archives. Classes include the three core classes - Work, Instance, and Item - in addition to many more classes to support description. Properties describe characteristics of the resource being described as well as relationships among resources. For example: one Work might be a "translation of" another Work; an Instance may be an "instance of" a particular Bibframe Work. Other properties describe attributes of Works and Instances. For example: the Bibframe property "subject" expresses an important attribute of a Work (what the Work is about), and the property "extent" (e.g. number of pages) expresses an attribute of an Instance.

A crystallography domain ontology based on EMMO and the CIF core dictionary. It is implemented as a formal language. (from https://nfdi4cat.org/services/ontologie-sammlung/)

A vocabulary describing licenses for data and code

Assigns identifiers to knowledge graphs (KGs) that are used and/or maintained within any NFDI consortium.

An ontology of qualifications, distinctions, and certifications that uses the Phenotype And Trait Ontology term quality (PATO:0000001) as a root term.

An open, community-driven registry of conference and event venues. EVR assigns persistent identifiers (PIDs) to make referencing venues FAIR. This is similar to how ORCID assigns PIDs to researchers and ROR assigns PIDs to research organizations. This benefits researchers assembling information about in-person conferences and events by enabling them to refer in an unambiguous way to the venue where it takes place. This repository follows the [Open Data, Open Code, Open Infrastructure (O3) principles](https://www.nature.com/articles/s41597-024-03406-w), meaning that the data and code are all in one repository that anyone can contribute to.

MIBiG (Minimum Information about a Biosynthetic Gene Cluster) is a data repository and associated data standard designed to describe biosynthetic gene clusters involved in the production of specialized metabolites. It also stores data on measured biological activities and links to other resources such as NCBI, NPAtlas, and ChEBI. MIBiG is used as a reference database, knowledgebase, and training dataset for machine learning.

The Science Data Discovery Ontology (sddo) is being developed to provide a semantic foundation for the discovery of information managed by NASA's Science Mission Directorate. This information spans many scientific disciplines, fields and subfields, including heliophysics, earth science, planetary science, astrophysics, biology, astrobiology, and physical science. [from repository]

Algorithm Metadata Vocabulary is a vocabulary for capturing and storing the metadata about the algorithms (a procedure or a set of rules that is followed step-by-step to solve a problem, especially by a computer). There are uncountable algorithms present in every area (e.g., Computer Science, Mathematics), which makes it hard for specialists, academicians, application engineers, and so forth to discover, distinguish, select, and reuse them. [from repository]

An ontology transcription of definitions in the Functional Mock-up Interface (FMI) standard document from https://fmi-standard.org/ that enables representing Functional Mock-up Units (FMUs) in RDF

The Reagent Ontology (ReO) adheres to OBO Foundry principles (obofoundry.org) to model the domain of biomedical research reagents, considered broadly to include materials applied “chemically” in scientific techniques to facilitate generation of data and research materials. ReO is a modular ontology that re-uses existing ontologies to facilitate cross-domain interoperability. It consists of reagents and their properties, linking diverse biological and experimental entities to which they are related. ReO supports community use cases by providing a flexible, extensible, and deeply integrated framework that can be adapted and extended with more specific modeling to meet application needs.