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This ontology provides the predicates necessary to describe an arrival of a transit vehicle and its departure at a certain Stop. @en
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This ontology represent context which may be interesting in providing recommendations to users. @en
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The CWRC Ontology is the ontology of the Canadian Writing Research Collaboratory. @en
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CTRLont specifies concepts and relationships of control actors on a high level @en
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This ontology defines classes and properties for describing participants, infrastructure, data and services of the International Data Spaces (formerly known as Industrial Data Space). @en
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The aim of the Occupant Feedback Ontology is to semantically describe passive and active occupant feedback and to enable integration of this feedback with linked building data. @en
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This ontology provides the terms necessary to describe the status of traffic lights. @en
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The process execution ontology is a proposal for a simple extension of both the [W3C Semantic Sensor Network](https://www.w3.org/TR/vocab-ssn/) and the [Semantic Actuator Network](https://www.irit.fr/recherches/MELODI/ontologies/SAN.owl) ontology cores. @en
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An ontology for describing programming language-specific runners, processors and pipelines in RDF-based data processing frameworks. @en
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Smart Building Evacuation Ontology (SBEO) is an ontology that couples the information about any building with its occupants such that it can be used in many useful ways. For example, indoor localization of people, detection of any hazard, a recommendation of normal routes such as shopping or stadium seating routes, or safe and feasible emergency evacuation routes or both of them all together. The core SBEO covers the concepts related to the geometry of building, devices and components of the building, route graphs correspondent to the building topology, users' characteristics and preferences, situational awareness of both building (hazard detection, status of routes in terms of availability and occupancy) and users (tracking, management of groups, status in terms of fitness), and emergency evacuation. @en
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The SEAS Building ontology describes a taxonomy of buildings, building spaces, and rooms. Some categorizations are based on the energy efficiency related to their insulation etc., although the actual values for classes depend the country specific regulations and geographical locations. Other categorizations are based on occupancy and activities. There is no single accepted categorization available. This taxonomy uses some types selected from: - International building occupancy based categories (USA) - The Classification of Types of Constructions (EU) - Finnish building categorization VTJ2000 (Finland) - Wikipedia category page for Rooms: https://en.wikipedia.org/wiki/Category:Rooms @en
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The Seas Trading Ontology defines concepts and relations to describe ownership, trading, bilateral contracts and market licenses: - players own systems and trade commodities, which have a price; - bilateral electricity contracts are connections between electricity traders at which they exchange electricity; - electricity markets are connections between electricity traders at which they exchange electricity, using a market license; - electricity markets can be cleared, and balanced; - evaluations can have a traded volume validity context @en
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ModSci is a reference ontology for modelling different types of modern sciences and related entities, such as scientific discoveries, renowned scientists, instruments, phenomena ... etc. @en
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An ontology to describe people and requests for timebanks. This includes the poeple's skills, limitations, and environment. @en
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With the aim of enhancing natural communication between workers in industrial environments and the systems to be used by them, TODO (Task-Oriented Dialogue management Ontology) has been developed to be the core of task-oriented dialogue systems. TODO is a core ontology that provides task-oriented dialogue systems with the necessary means to be capable of naturally interacting with workers (both at understanding and at ommunication levels) and that can be easily adapted to different industrial scenarios, reducing adaptation time and costs. Moreover, it allows to store and reproduce the dialogue process to be able to learn from new interactions. @en