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  • A Knowledge Model to describe a smart city, that interconnect data from infomobility service, Open Data and other source @en
  • The Open NEE Configuration Model defines a Linked Data-based model for describing a configuration supported by a Named Entity Extraction (NEE) service. It is based on the model proposed in "Configuring Named Entity Extraction through Real-Time Exploitation of Linked Data" (http://dl.acm.org/citation.cfm?doid=2611040.2611085) for configuring such services, and allows a NEE service to describe and publish as Linked Data its entity mining capabilities, but also to be dynamically configured. @en
  • This ontology is a specialization of the lifecycle vocabulary (http://purl.org/vocab/lifecycle/schema) meant to be used in the context of IoT. It is used as a module in the IoT core domain ontology IoT-O (www.irit.fr/recherches/MELODI/ontologies/IoT-O). IoT-Lifecycle adds a specific state definition (ParametrizedState) and a specific transition (Update) that is useful to model actuators. @en
  • CiteDCAT-AP is an extension of the DCAT application profile for data portals in Europe (DCAT-AP) for describing resources documented by using the DataCite metadata schema - the de facto standard for data citation, and used across scientific disciplines. Its basic use case is to make research data searchable on general data portals, thereby bridging the gap between scientific and public sector information. For this purpose, CiteDCAT-AP provides an RDF vocabulary and the corresponding RDF syntax binding for the metadata elements defined in DataCite. @en
  • This document is a vocabulary to describe compound measures, i.e. measures with several metric or item that are organized with serveral dimensions. The description of such a measure relies on a Tree-Structure of Requirement (TSoR): a set of requirements structured hierarchicaly with analysis element. A TSoR represents the main measure. Several information may be added to explicitely indicate how the overall score on the measure should be calculated based on the hierarchy, relative importance of the node of the hierarchy and an aggregation function. The measure can be described completely and unambiguously from the organisation to the requirements and the implementation. @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 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 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
  • 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
  • OPMW is a OPMV profile to model the executions and definitions of scientific workflows. @en
  • SAREF4INMA is an extension of SAREF for the industry and manufacturing domain. SAREF4INMA focuses on extending SAREF for the industry and manufacturing domain to solve the lack of interoperability between various types of production equipment that produce items in a factory and, once outside the factory, between different organizations in the value chain to uniquely track back the produced items to the corresponding production equipment, batches, material and precise time in which they were manufactured. SAREF4INMA is specified and published by ETSI in the TS 103 410-5 associated to this ontology file. SAREF4INMA was created to be aligned with related initiatives in the smart industry and manufacturing domain in terms of modelling and standardization, such as the Reference Architecture Model for Industry 4.0 (RAMI), which combines several standards used by the various national initiatives in Europe that support digitalization in manufacturing. The full list of use cases, standards and requirements that guided the creation of SAREF4INMA are described in the associated ETSI TR 103 507. @en
  • IoT-O is a core domain Internet of Things ontology. It is intended to model horizontal knowledge about IoT systems and applications, and to be extended with vertical, application specific knowledge. It is constituted of different modules : - A sensing module, based on W3C's SSN (http://purl.oclc.org/NET/ssnx/ssn) - An acting module, based on SAN (http://www.irit.fr/recherches/MELODI/ontologies/SAN) - A service module, based on MSM (http://iserve.kmi.open.ac.uk/ns/msm/msm-2014-09-03.rdf) and hRest (http://www.wsmo.org/ns/hrests) - A lifecycle module, based on a lifecycle vocabulary (http://vocab.org/lifecycle/schema-20080603.rdf) and an iot-specific extension (http://www.irit.fr/recherches/MELODI/ontologies/IoT-Lifecycle) - An energy module, based on powerOnt (ttp://elite.polito.it/ontologies/poweront.owl) IoT-O developping team also contributes to the oneM2M IoT interoperability standard. @en
  • Ontology for Cloud Computing Instances. Instance are classes of VM that comprise varying combinations of CPU, memory, storage, and networking capacity. This ontology allows to define the instantiation model of MVs used in large cloud computing providers such as Amazon, Azure, etc. @en
  • Ontology for the definition of regions and zones of availability on CloudComputing platforms and services. This ontology allows to define model of regions used in large cloud computing providers such as Amazon, Azure, etc. @en