Environments, earth science, geospatial data, sensors and observations.
The Environment Ontology is a resource and research target for the semantically controlled description of environmental entities. The ontology's initial aim was the representation of the biomes, environmental features, and environmental materials pertinent to genomic and microbiome-related investigations.
ECTO describes exposures to experimental treatments of plants and model organisms (e.g. exposures to modification of diet, lighting levels, temperature); exposures of humans or any other organisms to stressors through a variety of routes, for purposes of public health, environmental monitoring etc, stimuli, natural and experimental, any kind of environmental condition or change in condition that can be experienced by an organism or population of organisms on earth.
Ecocore is a community ontology for the concise and controlled description of ecological traits of organisms.
RBO is an ontology for the effects of radiation on biota in terrestrial and space environments.
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".
The Population and Community Ontology (PCO) describes material entities, qualities, and processes related to collections of interacting organisms such as populations and communities. It is taxon neutral, and can be used for any species, including humans. The classes in the PCO are useful for describing evolutionary processes, organismal interactions, and ecological experiments. Practical applications of the PCO include community health care, plant pathology, behavioral studies, sociology, and ecology.
A gazetteer constructed on ontological principles. The countries are actively maintained.
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.
It is a simple ontology to describe sequence feature positions and regions as found in GFF3, DBBJ, EMBL, GenBank files, UniProt, and many other bioinformatics resources
This ontology describes sensors, actuators and observations, and related concepts. It does not describe domain concepts, time, locations, etc. these are intended to be included from other ontologies via OWL imports.
The Plant Environment Ontology is a set of standardized controlled vocabularies to describe various types of treatments given to an individual plant / a population or a cultured tissue and/or cell type sample to evaluate the response on its exposure. It also includes the study types, where the terms can be used to identify the growth study facility.
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]
DataONE ontology of Carbon Flux measurements for MsTMIP and LTER Use Cases
Ontology of Zebrafish Experimental Conditions
This ontology extends the SAREF ontology for the environment domain, specifically for the light pollution domain, including concepts like photometers, light, etc.
BiodivRisk-Onto provides a formal OWL 2 DL representation of the semantic relations between four international biodiversity risk disclosure frameworks — TNFD, CSRD/ESRS E4, SBTN and GRI 101 — with particular attention to the data gaps arising from GBIF/OBIS sampling bias in Latin America and the Caribbean (LAC).
The controlled vocabulary of the CF metadata conventions, giving precise names, units and descriptions for climate, ocean and atmosphere variables in netCDF data.
The TERN Ontology comprises a set of vocabularies for representing plot-based ecological data. It was developed primarily based on the SOSA (Sensor, Observation, Sample, and Actuator) ontology. The TERN Ontology's classes and properties have been tailored to describe terrestrial ecology survey data including flora, vegetation and soil, following the methodologies outlined in the Australian Soil and Land Survey Field Handbook.
The Ontology for the Built Environment (OntoBuiltEnv) is an ontology developed for representing key information about properties (i.e. buildings as well as flats/apartments). It combines information about building usage, key construction characteristics, location and address, and estimated property value. More detailed geometric information can be retrieved from the associated OntoCityGml representation.
An ontology for representing geospatial information and design characteristics of manufacturing facilities and data centres operated by a company.
OntoEarthquake is an ontology developed to represent earthquake hazard
Ontology used to calculate exposures to the environment
Ontology to describe air quality and weather stations
The Environmental Thesaurus is a controlled vocabulary built to aid integration of the data resulting from long term ecological research and monitoring in Europe (eLTER). It provides described and semantically well defined terms for later analysis and it serves as harmonized specification of parameters in the observation and measurement of ecosystem processes.
Ontology for describing WiFi CSI measurements of human and machine activity captured in different environments.
The OGC GeoSPARQL standard supports representing and querying geospatial data on the Semantic Web. GeoSPARQL defines a vocabulary for representing geospatial data in RDF, and it defines an extension to the SPARQL query language for processing geospatial data. In addition, GeoSPARQL is designed to accommodate systems based on qualitative spatial reasoning and systems based on quantitative spatial computations.
This bilingual thesaurus organizes the key concepts of biodiversity sciences, in their basic and applied ecological components. It uses polyhierarchy and includes 818 reciprocal associative relationships. The 1654 French and English descriptors (designating 827 concepts) are enriched with a large number of synonyms (1860) and hidden variants (7020) in both languages. Concepts are grouped into 82 collections, by semantic categories, thematic fields and EBV classes (Essential Biodiversity Variables). Definitions are given with their sources.
The 'Scientific Observation Model' (CRMsci) is a formal ontology intended to serve as a global schema for integrating metadata about scientific observation, measurements, and processed data in descriptive and empirical sciences such as life sciences, geology, geography, archaeology, and cultural heritage conservation.
Lobbying Against Climate science Knowledge — a lightweight ontology for describing relationships between people and organisations relevant to lobbying against climate change awareness and policies.
The ontology and metadata schema for the NFDI4Earth Knowledge Hub. See serializations of this schema as an OWL ontology here: - [RDF/XML](https://nfdi4earth.pages.rwth-aachen.de/knowledgehub/nfdi4earth-kh-schema/ontology.owl.xml) - [RDF/Turtle](https://nfdi4earth.pages.rwth-aachen.de/knowledgehub/nfdi4earth-kh-schema/ontology.owl.ttl) - [RDF/JSON-LD](https://nfdi4earth.pages.rwth-aachen.de/knowledgehub/nfdi4earth-kh-schema/ontology.owl.jsonld) - [RDF/N-Triples](https://nfdi4earth.pages.rwth-aachen.de/knowledgehub/nfdi4earth-kh-schema/ontology.owl.nt)
This semantic artifact describes the semantic relationships between entities which model the setup of a biodiversity monitoring project based on capturing audiovisual digital recordings. It encodes the semantics of the Wildlife Monitoring Ontology and at the same time provides the datamodel behind the wildlive.senckenberg.de platform.
Use this database to browse the CMECS classification and to get definitions for individual CMECS Units. This database contains the units that were published in the Coastal and Marine Ecological Classification Standard.
The ontology of Cerrado wood plant dynamics was created in order to represent the set of concepts about the dynamics, that is, changes over time of the wood vegetation structure, of Cerrado. Ccon describes the main parameters used to measure the changes, such as mortality rate and recruitment rate. The Ccon is an OWL2 ontology according to the W3C recommendations [6], developed to represent the scientific knowledge about vegetation ecology focused to describe the dynamics of wood plants in the Brazilian Cerrado Domain.
The Semantic Web for Earth and Environmental Terminology is a mature foundational ontology that contains over 6000 concepts organized in 200 ontologies represented in OWL. Top level concepts include Representation (math, space, science, time, data), Realm (Ocean, Land Surface, Terrestrial Hydroshere, Atmosphere, etc.), Phenomena (macro-scale ecological and physical), Processes (micro-scale physical, biological, chemical, and mathematical), Human Activities (Decision, Commerce, Jurisdiction, Environmental, Research).
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Human
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Human Decision
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Human Environmental Assessment
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Human Environmental Conservation
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Human Environmental Control
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Human Environmental Standards
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Human Jurisdiction
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Human Knowledge Domain
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Human Research
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Human Technology Readiness
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Phenomena
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Phenomena Atmosphere
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Phenomena Atmosphere Cloud
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Phenomena Atmosphere Fog
Browse all 306 in the catalog →
Chemical Entities of Biological Interest (ChEBI) is a freely available dictionary of molecular entities focused on 'small' chemical compounds.
The OBO Relation Ontology provides consistent and unambiguous formal definitions of the relational expressions used in biomedical ontologies.
An OWL2 ontology of phenomena in infectious disease epidemiology and population biology for use in epidemic simulation.
Traits and phenotypes of flowering plants occurring in digitized Floras
The taxonomy contains the relationships between all living forms for which nucleic acid or protein sequence have been determined.
Zebrafish developmental stages ontology: Developmental stages of the Zebrafish. A ontology listed in Bioregistry, OBO Foundry, OLS (EMBL-EBI).
An ontology for describing the phenology of individual plants and populations of plants, and for integrating plant phenological data across sources and scales.
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.
ExO is intended to bridge the gap between exposure science and diverse environmental health disciplines including toxicology, epidemiology, disease surveillance, and epigenetics.
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.
Ontology representation of the [International Committee on Taxonomy of Viruses (ICTV)](https://ictv.global/) for the [EVORA project](https://evora-project.eu/)
The BioAssay Ontology (BAO) describes chemical biology screening assays and their results including high-throughput screening (HTS) data for the purpose of categorizing assays and data analysis.
The upper level ontology upon which OBO Foundry ontologies are built.
Ontologies that aim to provide semantic specifications for units of measure, quantity kind, dimensions and data types.
A structured controlled vocabulary of phenotypes of the slime-mould Dictyostelium discoideum.
The PMD Core Ontology (PMDco) is a comprehensive framework for representing knowledge that encompasses fundamental concepts from the domains of materials science and engineering (MSE). The PMDco has been designed as a mid-level ontology to establish a connection between specific MSE application ontologies and the domain neutral concepts found in established top-level ontologies. The primary goal of the PMDco is to promote interoperability between diverse domains.
An ontology of phenotypes covering microbes
PROCO (PROcess Chemistry Ontology) is a formal ontology that aims to standardly represent entities and relations among entities in the domain of process chemistry.
An ontology to support the interoperability of biodiversity data, including data on museum collections, environmental/metagenomic samples, and ecological surveys.
DCAT is an RDF vocabulary designed to facilitate interoperability between data catalogs published on the Web
The goal of the Systems Biology Ontology is to develop controlled vocabularies and ontologies tailored specifically for the kinds of problems being faced in Systems Biology, especially in the context of computational modeling. SBO is a project of the BioModels.net effort.
A representation of variables appearing in models in the environmental research space.
The namespace name http://www.w3.org/ns/prov# is intended for use with the PROV family of documents that support the interchange of provenance on the web.
Linked-data framework for connecting species in chemical kinetic reaction mechanisms with quantum calculations. A mechanism can be constructed from thermodynamic, reaction rate, and transport data that has been obtained either experimentally, computationally, or by a combination of both. In order to implement this approach, two existing ontologies, namely OntoKin, for representing chemical kinetic reaction mechanisms, and OntoCompChem, for representing quantum chemistry calculations, are extended. (from https://nfdi4cat.org/services/ontologie-sammlung/)
Other categories: Foundational & Upper Ontologies · Metadata, Provenance & Publishing · Life Sciences · Health & Clinical · Neuroscience · Chemistry & Materials · Agriculture, Food & Plants · Physical Sciences, Maths & Units · Engineering & Built Environment · Humanities & Culture · Privacy, Security & Law · Society, Government & Business · Computing & Software · Multidisciplinary & General
