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The REACT ontology aims to represent all the necessary knowledge to support the achievement of island energy independence through renewable energy generation and storage, a demand response platform, and promoting user engagement in a local energy community. The REACT ontology has been developed as part of the REACT project which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 824395. @en
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This ontology defines batteries and their state of charge ratio property. @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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An ontology to model accountability of AI systems which use machine learning. @en
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The Procedural Knowledge Ontology (PKO) addresses the Procedural Knowledge (PK) domain, and models procedures, their executions, and related resources and agents. @en
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This ontology defines: - a set of subclasses of `seas:Evaluation` to better interpret evaluations of quantifiable properties. - a set of sub properties of `seas:hasProperty` to qualify time-related properties. @en
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Quality, architecture, and process are considered the keystones of software engineering. ISO defines them in three separate standards. However, their interaction has been poorly studied, so far. The SQuAP model (Software Quality, Architecture, Process) describes twenty-eight main factors that impact on software quality in banking systems, and each factor is described as a relation among some characteristics from the three ISO standards. Hence, SQuAP makes such relations emerge rigorously, although informally. SQaAP-Ont is an OWL ontology that formalises those relations in order to represent and reason via Linked Data about software engineering in a three-dimensional model consisting of quality, architecture, and process characteristics. @en
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A vocabulary specifying concepts and structures needed to represent different data cubes needed for the Smart Readiness Indicator. @en
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An ontology to describe a Semantic-Web Machine Learning System (SWeMLS) @en
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An Ontology for the Statbarn Framework used in Output Statistical Disclosure Control (OSDC). @en
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A hypermedia specification for fragmenting collections. @en
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The goal of this module is to represent the equipment hierarchy model involved in the tribological experiments. @en
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The goal of this module is to represent the materials that can be involved in the tribological experiments as part of the tested samples. @en
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The goal is to represent the tribological experiments by relaying on the representation included in the core,, sample and equipment modules. @en
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The goal of this module is to represent the common classes, and object and data properties included in two or more modules of the TribOnt ontology. @en