150
results
-
The SEAS Device ontology defines `seas:Device` as physical system that are designed to execute one or more procedures that involve the physical world. @en
-
This ontology defines feature of interest and their properties, as an extension of the core classes of the SSN ontology (https://www.w3.org/ns/ssn/). A feature of interest is an abstraction of a real world phenomena (thing, person, event, etc). A feature of interest is then defined in terms of its properties, which are qualifiable, quantifiable, observable or operable qualities of the feature of interest. Alignments to other ontologies are proposed in external documents: - [SSNAlignment](https://w3id.org/seas/SSNAlignment) proposes an alignment to the [SSN ontology](http://www.w3.org/ns/ssn/). - [QUDTAlignment](https://w3id.org/seas/QUDTAlignment) proposes an alignment to the [QUDT ontology](http://qudt.org/). @en
-
The SEAS Operating Ontology defines evaluations of operating features of interest. @en
-
This ontology defines proposed alignemnts with the QUDT ontology. @en
-
This ontology defines common evaluation interpretation concepts for statistics. @en
-
The System Ontology defines Systems, Connections between systems, and Connection Points at which systems may be connected. This ontology is then specialized for multiple domains. For example: - In electric energy: - power systems consume, produce, store, and exchange electricity; - power connections are where electricity flows between systems; - power connection points are plugs, sockets, or power busses. - In the electricity market: - players and markets are systems; - connections are contracts or transactions between two players, or between a player and a market; - connection points include offers and bids. @en
-
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
-
This vocabulary is version v0.1 of the ITEA2 Smart Energy Aware Systems project vocabulary. It enables the description of electricity measurements of a site using the Data Cube W3C vocabulary. @en
-
This ontology defines batteries and their state of charge ratio property. @en
-
The Procedural Knowledge Ontology (PKO) addresses the Procedural Knowledge (PK) domain, and models procedures, their executions, and related resources and agents. @en
-
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
-
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
-
gist is a minimalist upper ontology created by Semantic Arts. @en
-
OWL 2 ontology modeling the 3GPP RAN standardization document lifecycle (Tdoc, Resolution, CR, LS, Section, Spec, TechnicalReport, TRImpact, Meeting, Company, WorkingGroup). Designed from RAN1 competency questions and validated by cross-WG instantiation against RAN2-RAN5 with no additional process-layer classes required. Also declares six entity-layer classes (RRCParameter, CapabilityItem, Feature, Procedure, PerformanceRequirement, ConformanceTest) modeling spec-body entities: ASN.1 IEs, UE capability items, named standardization features, protocol procedures, performance requirements, and conformance test specifications. @en
-
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