Ontologies

ISO 10303 provides a representation of product information along with the necessary mechanisms and definitions to enable product data to be exchanged. The exchange is among different computer systems and environments associated with the complete product lifecycle, including product design, manufacture, use, maintenance, and final disposition of the product. This document defines the basic principles of product information representation and exchange used in ISO 10303. It specifies the characteristics of the various series of parts of ISO 10303 and the relationships among them.

This standard extends IEEE 1872-2015 Standard for Ontologies for Robotics and Automation to represent additional domain-specific concepts, definitions, and axioms commonly used in Autonomous Robotics (AuR). This standard is general and can be used in many ways - for example, to specify the domain knowledge needed to unambiguously describe the design patterns of AuR systems, to represent AuR system architectures in a unified way, or as a guideline to build autonomous systems consisting of robots operating in various environments.

The Energy Grid ontology
describes power stations, substations, energy resources, and
customers.

We collaborated with Open Agile Smart Cities (OASC) and Sirus to provide DTDL-based onotlogy, starting with ETSI CIM NGSI-LD, and accelerate accelerate development of digital twins-based solutions for smart cities. In addition to ETSI NGSI-LD, we-ve also evaluated Saref4City, CityGML, ISO and others.
The ETSI CIM NGSI-LD specification defines an open framework for context information exchange named NGSI-LD which comes with an information model that defines the meaning of the most needed terms, and a domain-specific extension to model any information. The core meta-model provides a basis for representing property graphs using RDF/RDFS/OWL, and is formed of Entities, their Relationships, and their Properties with values, encoded in JSON-LD.

This DTDL ontology is implemented based on the domain ontology RealEstateCore. RealEstateCore is a common language used to model and control buildings, simplifying the development of new services. The ontology is rich and complete, while providing simplicity and real-world applicability with proven industry solutions and partnerships. It has seen practical deployments across sizeable real estate portfolios over the past several years, and has gone through several revisions based on real-world feedback and learning. RealEstateCore specifically does not aim to be a new standard, but rather provides a common denominator and bridge with other building industry standards such as Brick Schema, Project Haystack, W3C Building Topology Ontology (W3C BOT), and more. Read more about our ontology alignment with standards. The original RealEstateCore ontology is represented using the W3C Web Ontology Language (OWL) and it can be visualized here. It has been converted into the DTDL syntax used in this repository using our universal OWL2DTDL tool.

The Common Information Model (CIM) is an electric power transmission and distribution standard developed by the electric power industry. It aims to allow application software to exchange information about an electrical network. It has been officially adopted by the International Electrotechnical Commission (IEC).

This document establishes general principles and gives guidelines for an indicator upper level ontology (IULO) for smart cities that enables the representation of indicator definitions and the data used to derive them. It includes: concepts (e.g., indicator, population, cardinality); and properties that relate concepts (e.g., cardinality_of, parameter_of_var).

VSSo derives from the automotive standard VSS, and follows the SSNpattern for representing observations and actuations. VSSo defines car components, sensors, signals, etc.

This document specifies the structure of an ontology for a fine-grained description of the expressive power of corpus query languages (CQLs) in terms of search needs. The ontology consists of three interrelated taxonomies of concepts: the CQLF metamodel (a formalization of ISO24623-1); the expressive power taxonomy, which describes different facets of the expressive power of CQLs; and a taxonomy of CQLs. This document specifies: a) the taxonomy of the CQLF metamodel; b) the topmost layer of the expressive power taxonomy (whose concepts are called functionalities); c) the structure of the layers of the expressive power taxonomy and the relationships between them, in the form of subsumption assertions; d) the formalization of the linkage between the CQL taxonomy and the expressive power taxonomy, in the form of positive and negative conformance statements. This document does not define the entire contents of the ontology (see <a>Clause4</a>).

ISO 21127:2014 establishes guidelines for the exchange of information between cultural heritage institutions. In simple terms, this can be defined as the information managed by museums, libraries, and archives. The intended scope of this ISO 21127:2014 is defined as the exchange and integration of heterogeneous scientific documentation relating to museum collections. This definition requires further elaboration.

ISO 37120 - Sustainable Development and Resilience of Communities - Indicators for City Services and Quality of Life (under TC268) http://ontology.eil.utoronto.ca/ISO37120.html. This OWL file defines a class for each indicator defined in the ISO 37120 standard. Names for each indicator are provided. Text definitions are provided only for Economy, Education and Energy indicators, due to copyright restrictions imposed by ISO. This file is meant to provide a single URI for each indicator. An ontology for representing an indicator's supporting data plus meta information such as provenance, validity and trust can be found in: http://ontology.eil.utoronto.ca/GCI/Foundation/GCI-Foundation.owl Documentation of the ontology can be found in: http://eil.utoronto.ca/smartcities/papers/GCI-Foundation-Ontology.pdf

The Plant Ontology is a structured vocabulary and database resource that links plant anatomy, morphology and growth and development to plant genomics data.