BCIOThe Behaviour Change Intervention Ontology
The Behaviour Change Intervention Ontology is an ontology for all aspects of human behaviour change interventions and their evaluation.
Smart devices, buildings, the Internet of Things and industrial data.
The Behaviour Change Intervention Ontology is an ontology for all aspects of human behaviour change interventions and their evaluation.
OEO is a domain reference ontology for energy system modeling.
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.
The IOF Core Ontology contains notions found to be common across multiple manufacturing domains. This file is an RDF implementation of these notions. The ontology utilizes the Basic Formal Ontology or BFO as a top-level ontology but also borrows terms from various domain-independent or mid-level ontologies. The purpose of the ontology is to serve as a foundation for ensuring consistency and interoperability across various domain-specific reference ontologies the IOF publishes.
Vitro is a full stack framework for building semantic web applications. It is not domain specific.
Brick is an open-source effort to standardize semantic descriptions of the physical, logical and virtual assets in buildings and the relationships between them. Brick consists of an extensible dictionary of terms and concepts in and around buildings, a set of relationships for linking and composing concepts together, and a flexible data model permitting seamless integration of Brick with existing tools and databases.
An EMMO-based domain ontology for atomistic and electronic modelling.
A battery interface domain ontology based on EMMO.
gist is a minimalist upper ontology created by Semantic Arts.
Controlled vocabulary for the classification of the theme for a mobility dataset.
This ontology aims to model the Web of Things domain according to the W3C Interest Group (http://w3c.github.io/wot/)
This ontology extends the SAREF ontology for the building domain by defining building devices and how they are located in a building. This extension is based on the ISO 16739:2013 Industry Foundation Classes (IFC) standard for data sharing in the construction and facility management industries. The descriptions of the classes and properties extracted from IFC have been taken from the IFC documentation.
This ontology extends the SAREF ontology for the water domain. This work has been developed in the context of the STF 566, which was established with the goal to create three SAREF extensions, one of them for the water domain.
SAREF4WEAR is an extension of SAREF for Wearables
This ontology extends the SAREF ontology for the automotive domain. This work has been developed in the context of the STF 566, which was established with the goal to create four SAREF extensions, one of them for the automotive domain.
This is the extension of SAREF for the EEBus and Energy@Home project. The documentation of SAREF4EE is available at http://ontology.tno.nl/SAREF4EE_Documentation_v0.1.pdf. SAREF4EE represents 1) The configuration information exchanged in the use case 'Remote Network Management' according to the EEBus Technical Report, Protocol Specification- Remote Network Management, version 1.0.0.2, 2015-09-19;
The objective of SAREF4EHAW is to extend SAREF ontology for the eHealth/Ageing-well (EHAW) vertical. Clause 4.1 of the present document shortly introduces a high level view of the envisioned SAREF4EHAW semantic model and modular ontology, with the retained concepts (i.e. classes) and their relations.
This ontology extends the SAREF ontology for the smart grid domain.
SAREF4INMA is an extension of SAREF for the industry and manufacturing domain. SAREF4INMA focuses on extending SAREF for the industry and manufacturing domain to solve the lack of interoperability between various types of production equipment that produce items in a factory and, once outside the factory, between different organizations in the value chain to uniquely track back the produced items to the corresponding production equipment, batches, material and precise time in which they were manufactured.
This ontology extends the SAREF ontology for the Smart Lifts domain.
Domain ontology for transforming UAM flight records into governable, valuatable, and tradable data assets. The ontology distinguishes raw flight evidence from governed asset candidates, aggregated data products, and revenue-right objects.
The Smart Applications REFerence ontology (SAREF) is intended to enable interoperability between solutions from different providers and among various activity sectors in the Internet of Things (IoT), thus contributing to the development of the global digital market.
The Building Information Modelling ontology (OntoBIM) is an ontology developed to represent the detailed information and spatial relationships of buildings and their components (walls, doors, roofs, furniture, equipment) that is available in the Industry Foundation Classes (IFC) data schema. Information about their individual characteristics such as material, readings, and dimensions is combined from IFC or other data sources.
A WorldAvatar ontology describing building management systems
The Building Structure ontology (OntoBuildingStructure) is an ontology developed to represent the building structural components (walls, doors, slabs, roofs, stairs) and their individual characteristics such as dimensions and qualities.
OntoDevice is an ontology for describing devices, their capabilities and properties.
OntoEnergySystem is an ontology developed for representing energy systems.
An ontology developed for representing potential energy surface scans.
Ontology for urban building energy modelling (UBEM) and master planning (MP) data
PRO Research: An ontology for describing RDM-Policies in a structured way
This ontology extends the SAREF ontology for the Smart City domain. This work has been developed in the context of the STF 534 (https://portal.etsi.org/STF/STFs/STFHomePages/STF534.aspx), which was established with the goal to create three SAREF extensions, one of them for the Smart City domain.
The present document is the technical specification of SAREF4SYST, a generic extension of [ETSI TS 103 264 SAREF](https://www.etsi.org/deliver/etsi_ts/103200_103299/103264/02.01.01_60/ts_103264v020101p.pdf) that defines an ontology pattern which can be instantiated for different domains. SAREF4SYST defines Systems, Connections between systems, and Connection Points at which systems may be connected. These core concepts can be used generically to define the topology of features of interest, and can be specialized for multiple domains.
SAREF4MARI is an extension of SAREF for the maritime domain.
A semantic framework for occupant-centric building control. This ontology is under active development and has not yet been fully validated.
A World Avatar ontology describing building duct behavior
A WorldAvatar ontology for classifying time-series measurements into states/ranges such as Low, Normal, High, Rising, and Falling
BIMxel is a thin integration layer over established built-environment and IoT ontologies: it does not redefine what a building, a sensor, or an organization is. It aligns its own small vocabulary to BOT, BEO, SAREF (and SAREF4BLDG/SAREF4CITY/SAREF4WATR/SAREF4ENER), PROV-O, DCAT, schema.org, and the pi.pauwel.be MEP/distribution-element vocabulary, adding only the handful of terms none of those already cover. See the Example section of this documentation for a real, annotated instance-data walkthrough.
An ontology for knowledge exchange between product designers and recyclers to improve consideration of recycling in product design.
This subject heading system has beeen developed for use in FID BAUdigital and its future web services. It covers scientific fields of Civil Engineering, Architecture and Urban Studies with a special section on digitization. This subject classification has been mapped to several other classification systems. The latest version of the subject classification including these mappings is available at https://gitlab.com/fid-bau/terminologie/fid-baudigital-faecherklassifikation/-/raw/main/Subject_Headings_all_mappings.owl.
SARGON2 ontology represents the energy domain including building and non-energy domain including weather and serve as the extension of other ontologies for the digital services in the energy sector, and enable the seamless semantic integration of energy assets in Renewable Energy Valleys. This ontology also fouces on the renewable energy resources including biomass, biogas, wind, solar, geothermal, and hydrogen entities. The main focus of this ontology is to cover the necessary components in the power systems by aligning with IEC61970CIM standard.
Concepts for a categorization reflecting the format of the storage medium and housing of a carrier in combination with the type of intermediation device required to view, play, run, or otherwise access the content of a manifestation.
Concepts for a format that is used in the production of a projected image.
Concepts for a process that is used to produce a manifestation.
Concepts for a designation for one or more regions of the world for which a videodisc or video game carrier has been encoded, indicating that playback is restricted to a device configured to decode it.
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Phenomena Energy
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Property Energy
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Property Energy Flux
The Semantic Web for Earth and Environmental Terminology (SWEET) ontology for Representation Data Product
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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.
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.
FIBO defines the sets of things that are of interest in financial business applications and the ways that those things can relate to one another. In this way, FIBO can give meaning to any data (e.g., spreadsheets, relational databases, XML documents) that describe the business of finance
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.
The Potential Drug-drug Interaction and Potential Drug-drug Interaction Evidence Ontology
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)
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.
PROCO (PROcess Chemistry Ontology) is a formal ontology that aims to standardly represent entities and relations among entities in the domain of process chemistry.
The ontology Metadata4Ing is developed within the NFDI Consortium NFDI4Ing with the aim of providing a thorough framework for the semantic description of research data, with a particular focus on engineering sciences and neighbouring disciplines. This ontology allows a description of the whole data generation process (experiment, observation, simulation), embracing the object of investigation, all sample and data manipulation procedures, a summary of the data files and the information contained, and all personal and institutional roles.
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 Livestock Product Trait Ontology (LPT) is a controlled vocabulary for the description of traits (measurable or observable characteristics) pertaining to products produced by or obtained from the body of an agricultural animal or bird maintained for use and profit.
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]
Comprehensive hierarchy of extinct and extant vertebrate taxa.
DataONE ontology of Carbon Flux measurements for MsTMIP and LTER Use Cases
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/)
Represents chemical kinetic reaction mechanisms.
This ontology extends the SAREF ontology for the environment domain, specifically for the light pollution domain, including concepts like photometers, light, etc.
An ontology developed for representing crop energy data.
nmrCV is a controlled vocabulary to deliver standardized descriptors for the open mark-up language for NMR raw and spectrum data, sanctioned by the metabolomics standards initiative msi.
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.
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 ontology extends the SAREF ontology for the Agricultural domain. This work has been developed in the context of the STF 534 (https://portal.etsi.org/STF/STFs/STFHomePages/STF534.aspx), which was established with the goal to create three SAREF extensions, one of them for the Agricultural domain.
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