UOUnits of measurement ontology
An ontology of units of measurement, used across OBO Foundry ontologies to annotate quantitative values with standard units.
Quantities and units of measure, mathematics, statistics, physics and astronomy.
An ontology of units of measurement, used across OBO Foundry ontologies to annotate quantitative values with standard units.
Ontologies that aim to provide semantic specifications for units of measure, quantity kind, dimensions and data types.
The ExPaNDS Photon and Neutron Experimental Techniques (PaNET) ontology provides a taxonomy and thesaurus of photon and neutron (PaN) experimental techniques. Based mainly on accelerator-based light sources and neutron facilities, the primary use of the ontology is to enhance the FAIRness of PaN data catalogues services. The ontology defines specific techniques in terms of more general technique classes and provides synonyms and references.
The Unified Astronomy Thesaurus (UAT) is an open, interoperable and community-supported thesaurus being developed to unify the existing divergent and isolated Astronomy & Astrophysics thesauri into a single high-quality, freely-available open-source thesaurus which will be of immediate value to both research and research support, and provide a mechanism for reviewing, discussing and evaluating the continuous evolution of terminology in these fields.
MathModDB is a database of mathematical models developed by the Mathematical Research Data Initiative (MaRDI). MathModDB defines a data model with classes (Mathematical Model, Mathematical Formulation, Research Field, Research Problem, Quantity [Kind], Computational Task, Publication), object properties/relations, data properties and annotation properties as an ontology. This ontology is populated with individuals/data from various fields of applied mathematics, making it a knowledge graph. [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.
The Experimental Measurements, Purposes, and Treatments ontologY (EMPTY) is a structured vocabulary designed to capture and standardize the scientific reasoning behind experimental measurements. It addresses a critical gap in existing metadata standards, which primarily focus on technical specifications rather than scientific intent. The ontology provides a common language to express why a measurement was taken and the conceptual conditions under which it should be interpreted.
PhySH (Physics Subject Headings) is a physics classification scheme developed by the American Physical Society to organize journals, meetings, and other content by topic. The development of PhySH is motivated by the lack of a fully open, high quality classification scheme for physics. It is intended initially to meet the specific goals of the APS for our journal, meeting, and other content. A longer term goal is to make it available for use by the broader community.
A small extension of CIDOC CRM and LRMoo for digital editions of piano rolls. It adds the symbols a reproducing piano reads from a roll (notes and expression commands), the relations between such symbols that an editor states, and the edits by which one version of a roll becomes another. Everything else (physical copies and their holes, recording processes, versions, editorial beliefs) is expressed with CIDOC CRM, LRMoo and CRMinf directly. The closed value lists of the format are the types at https://w3id.org/reo/type/.
The WorldAvatar ontology for traffic incidents and descriptive statistics
Ontology, part of the SI Reference Point, covering measurement units (SI base units and SI units with special names).
Ontology, part of the SI reference point, covering the seven underpinning constants of the SI
Ontology, part of the SI Reference Point, covering the historical decisions of the BIPM concerning measurement units.
Ontology, part of the SI reference point, covering kinds of quantities.
Ontology, part of the SI Reference Point, covering prefixes for the SI measurement units.
Ontology, part of the SI Reference Point, covering measurement units (SI base units and SI units with special names) and prefixes.
The Ontology of units of Measure (OM) 2.0 models concepts and relations important to scientific research. It has a strong focus on units, quantities, measures, and dimensions.
This vocabulary and grammar defines which types of objects are admissible to the MathAlgoDB - the algorithm knowledge graph - and by which properties they can relate. All in all five classes, "problem", "algorithm", "benchmark", "software", "publication", are defined, as well as a minimal but intuitively intelligible number of properties. As opposed to the more liberal WikiData, MathAlgoDB relies on the strict adherence to the ontology to provide a reliable machine-readable database of (numerical) algorithm knowledge. [from homepage]
OWL 2 ontology derived from the PV-Collada 2.0 XSD schema. Provides vocabulary for PV system circuit topology, physical layout geometry, and component product data, within the MDS-Onto builtenv domain.
Concepts for a type of unit or subunit of a manifestation.
Concepts for a unit of chronological duration that is used in the names and access points of calendrical timespans.
Concepts for the physical format of the encasing for the storage medium.
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Process Physical
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Property Quantity
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Realm Astrophysical
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Realm Astrophysical Body
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Realm Astrophysical Heliosphere
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Relationships Mathematical
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Relationships Physical
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Representation Mathematics
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Representation Mathematics Function
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Representation Mathematics Function Orthogonal
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Representation Mathematics Graph
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Representation Mathematics Operation
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Representation Mathematics Solution
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Representation Mathematics Statistics
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Representation Scientific Units
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for State Physical
PhyDiT provides the bare-essential classes and relationships which bridge to ontologies for control program description (like CTRLOnt, CDL etc.), system design description (like BRICK, SOSA, etc.), and physical process models (like OntoCAPE, Tubes, Flow etc.)
Spec Terms provides classes and properties that can be used to describe any significant unit of information in technical reports.
The Historic Structure Ontology (HSTO) provides a formal representation of the physical configuration of masonry aggregates by explicitly modelling the relationships among their structural components, including facades, horizontal structures, openings, and connections.
NeXus is a common data format for neutron, x-ray, and muon experimental data. The NeXus Ontology is an ontology representation of the NeXus [definitions](https://github.com/nexusformat/definitions/).The [NeXus International Advisory Committee](https://www.nexusformat.org/NIAC.html) is responsible for NeXus.
An OSH design-space and physical world ontology
The plasma ontology (Plasma-O) supports the standardized documentation of research data in the field of plasma physics. In accordance with typical plasma processes and applications, the ontology contains terminologicial knowledge about plasma source, plasma medium, and plasma target. Furthermore, metadata for the respectively applied diagnostic and modelling/simulation methods are represented.
This ontology extension was created to address the following needs: - The necessity of expressing time-series of data for various tasks and services in InterConnect - A workable and unambiguous characterization of quantities, combining units with measurements. This characterization should be technically complete so that quantities cannot be confused during data exchange between unfamiliar services
It is used to define the topological location (e.g., grid segment, market segment, regulation zone, ...) associated to a Forecast, a Timeseries or a DataPoint. It speciies where a measurement was made, for example a forecast might be valid for a specific region or grid segment.
Extension of the Ontology of Units of Measure (OM) with common units used in the Interconnect project
An extension of SKOS for representaion of nomenclatures
Browse all 54 in the catalog →
STATO is the statistical methods ontology. It contains concepts and properties related to statistical methods, probability distributions and other concepts related to statistical analysis, including relationships to study designs and plots.
Conditions under which physiological and morphological measurements are made both in the clinic and in studies involving humans or model organisms.
CHMO, the chemical methods ontology, describes methods used to
Morphological and physiological measurement records generated from clinical and model organism research and health programs.
The Experimental Factor Ontology (EFO) provides a systematic description of many experimental variables available in EBI databases. It combines parts of several biological ontologies, such as anatomy, disease and chemical compounds. The scope of EFO is to support the annotation, analysis and visualization of data handled by the EBI Functional Genomics Team.
A representation of the variety of methods used to make clinical and phenotype measurements.
OBCS stands for the Ontology of Biological and Clinical Statistics. OBCS is an ontology in the domain of biological and clinical statistics. It is aligned with the Basic Formal Ontology (BFO) and the Ontology for Biomedical Investigations (OBI)
A structured controlled vocabulary for cross-linking reagents used with proteomics mass spectrometry.
Owl-time is an owl-2 dl ontology of temporal concepts, for describing the temporal properties of resources in the world or described in web pages. the ontology provides a vocabulary for expressing facts about topological (ordering) relations among instants and intervals, together with information about durations, and about temporal position including date-time information.
An ontology for representing the provenance of scientific claims and the evidence that supports them.
The upper level ontology upon which OBO Foundry ontologies are built.
An ontology and inventory of geopolitical entities such as nations and their components (states, provinces, districts, counties) and the actual physical territories over which they have jurisdiction. We thus distinguish and assign different identifiers to the US in "The US declared war on Germany" vs. the US in "The plane entered US airspace".
an application ontology for supporting description and annotation of mass-spectrometry and nmr-spectroscopy based metabolomics experiments and fluxomics studies.
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)
The eNanoMapper project (https://www.enanomapper.net/), NanoCommons project (https://www.nanocommons.eu/) and ACEnano project (http://acenano-project.eu/) are creating a pan-European computational infrastructure for toxicological data management for ENMs, based on semantic web standards and ontologies. This ontology is an application ontology targeting the full domain of nanomaterial safety assessment. It re-uses several other ontologies including the NPO, CHEMINF, ChEBI, and ENVO.
An ontology that represents the basic knowledge of physical, chemical and functional characteristics of nanotechnology as used in cancer diagnosis and therapy.
An ontology to represent genomics cohort attributes.
This ontology is based on the SSN Ontology by the W3C Semantic Sensor Networks Incubator Group (SSN-XG), together with considerations from the W3C/OGC Spatial Data on the Web Working Group.
The Brenda tissue ontology is a structured controlled vocabulary eastablished to identify the source of an enzyme cited in the Brenda enzyme database. It comprises terms of tissues, cell lines, cell types and cell cultures from uni- and multicellular organisms.
The Vital Sign Ontology (VSO) is an extension of the Ontology for General Medical Science (OGMS). VSO covers the four consensus human vital signs: blood pressure, body temperature, respiration rate, pulse rate. VSO provides also a controlled structured vocabulary for describing vital signs measurement data, the various processes of measuring vital signs, and the various devices and anatomical entities participating in such measurements.
The Foundational Model of Anatomy Ontology (FMA) is a biomedical informatics ontology. It is concerned with the representation of classes or types and relationships necessary for the symbolic representation of the phenotypic structure of the human body. Specifically, the FMA is a domain ontology that represents a coherent body of explicit declarative knowledge about human anatomy.
An ontology of physico-chemical processes, i.e. physico-chemical changes occurring in course of time.
The controlled vocabulary of the CF metadata conventions, giving precise names, units and descriptions for climate, ocean and atmosphere variables in netCDF data.
An ontology of physico-chemical methods and properties.
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