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results
  • Ontology for the orchestration of the aerOS continuum. @en
  • Simple ontology for Cloud Computing Services. This ontology allows to define model of prices used in large cloud computing providers such as Google, Amazon, Azure, etc., including options for regions, type of instances, prices specification, etc. @en
  • domOS Common Ontology (dCO) represents a common information model to share a unified understanding for humans and machines and to ensure semantic interoperability in a heterogeneous IoT infrastructure. This ontology allows the decoupling of the infrastructure from the software services and applications. @en
  • The scope of the DIO is the domain of design intent or design rationale that needs to be documented while undertaking the design of any artifact @en
  • Digital Twin ontology used to define Digital Twins and Semantic Digital Twins and aggregations by dimensions using Web of Things. @en
  • The DINGO ontology (Data Integration for Grant Ontology) defines the terms of the DINGO vocabulary and provides a machine readable extensible framework to model data relative to projects, funding, project and funding actors, and, notably, funding policies. It is designed to yield high modeling power and elasticity to cope with the huge variety in funding and project practices, which makes it applicable to many areas where funding is an important aspect: first of all research, but also the arts, cultural conservation, and many others. @en
  • The DNS Security Ontology (DSecO) project is a data model for representing and reasoning on Domain Name System (DNS) data. The ontology is developed using web technologies (e.g. RDF, OWL, SKOS) and is intended as a structure for realizing a DNS Knowledge Graph (KG) for administration and security assessment applications. The model has been developed in collaboration with operational teams, and in connection with third parties linked vocabularies. Alignment with third parties vocabularies is implemented on a per class or per property basis when relevant (e.g. with `rdfs:subClassOf`, `owl:equivalentClass`). Directions for direct instanciation of these vocabularies are provided for cases where implementing a class/property alignment is redundant. Alignment holds for the following vocabulary releases: - [ORG](https://www.w3.org/TR/vocab-org/) 0.8 - [UCO](https://github.com/ucoProject/uco) Release-0.8.0 @en
  • The Geometry Metadata Ontology contains terminology to Coordinate Systems (CS), length units and other metadata (file size, software of origin, etc.). GOM is designed to be at least compatible with OMG (Ontology for Managing Geometry) and FOG (File Ontology for Geometry formats), and their related graph patterns. In addition, GOM provides terminology for some experimental data structures to manage (marked as vs:term_status = unstable): * transformed geometry (e.g. a prototype door geometry that is reused for all doors of this type). This is closely related to the transformation of Coordinate Systems @en
  • The Heat Pump Ontology (HPOnt) aims to formalize and represent all the relevant information of Heat Pumps. The HPOnt 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
  • PROV extension for linking Plans and parts of plans to their respective executions. @en
  • The File Ontology for Geometry formats (FOG) describes meaningful relations towards geometry snippets in RDF literals, geometry files on relative or absolute URLs and ontology-based geometry descriptions. The defined properties in this ontology are related towards each other and additional metadata is provided, such as file extension and related specifications/sources (incl. entries in dbpedia and Wikidata). The initial version of the ontology (v0.0.1) was documented in: Bonduel, Mathias, Wagner, Anna, Pauwels, Pieter, Vergauwen, Maarten, & Klein, Ralf (2019). Including Widespread Geometry Formats in Semantic Graphs Using RDF Literals. In Proceedings of the European Conference on Computing in Construction (EC3 2019). Chania, Greece. @en
  • CTRLont specifies concepts and relationships of control actors on a high level @en
  • 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
  • OWL ontology for the IFC conceptual data schema and exchange file format for Building Information Model (BIM) data @en
  • The Ontology for Property Management (OPM) extends the concepts introduced in the Smart Energy Aware Systems (SEAS) Evaluations ontology. @en