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.
ISO 14199:2015 defines a set of models collectively referred to as the Biomedical Research Integrated Domain Group (BRIDG) model for use in supporting development of computer software, databases, metadata repositories, and data interchange standards. It supports technology solutions that enable semantic (meaning-based) interoperability within the biomedical/clinical research arena and between research and the healthcare arena. The clinical research semantics are represented as a set of visual diagrams which describe information relationships, definitions, explanations, and examples used in protocol-driven biomedical research. These diagrams are expressed using the iconography and grammar of the Unified Modelling Language (UML), the HL7 Reference Information Model (RIM), and a Web Ontology Language (OWL). ISO 14199:2015 establishes the links between protocol-driven research and its associated regulatory artefacts including the data, organization, resources, rules, and processes involved in the formal assessment of the utility, impact, or other pharmacological, physiological, or psychological effects of a drug, procedure, process, subject characteristic, or device on a human, animal, or other subject or substance along with all associated regulatory artefacts required for or derived from this effort, including data specifically associated with post-marketing adverse event reporting.
ISO 14199:2015 defines a set of models collectively referred to as the Biomedical Research Integrated Domain Group (BRIDG) model for use in supporting development of computer software, databases, metadata repositories, and data interchange standards. It supports technology solutions that enable semantic (meaning-based) interoperability within the biomedical/clinical research arena and between research and the healthcare arena. The clinical research semantics are represented as a set of visual diagrams which describe information relationships, definitions, explanations, and examples used in protocol-driven biomedical research. These diagrams are expressed using the iconography and grammar of the Unified Modelling Language (UML), the HL7 Reference Information Model (RIM), and a Web Ontology Language (OWL).
CASO (Context Aware System Observation) is an ontology for context aware system and observation services. Its goal is to describe all the processing of the context.
This trial-use standard defines a standardized method for the design of quantum algorithms. The defined methods apply to any type of algorithm that can be assimilated into quantum primitives and/or quantum applications. The design of the algorithms is done preceding quantum programming.
This document specifies a taxonomy and an ontology for blockchain and distributed ledger technologies (DLT). The taxonomy includes a taxonomy of concepts, a taxonomy of DLT systems and a taxonomy of application domains, purposes and economy activity sections for use cases. The ontology includes classes and attributes as well as relations between concepts. The audience includes but is not limited to academics, architects, customers, users, tool developers, regulators, auditors and standards development organizations.
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.
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.
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.
Defines a formal logic based concept specialisation approach to support the development of manufacturing reference models that can underpin the necessary business specific knowledge models that are needed to support the configuration of global production networks.