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The Advene project aims at providing a model and various formats to share annotations about digital video documents (movies, courses, conferences...), as well as tools to edit and visualize the hypervideos generated from both the annotations and the audiovisual documents. Teachers, moviegoers, etc. can use them to exchange multimedia comments and analyses about video documents. The Cinelab model allows not only to represent video annotations, but also an elicitation of their structure (through notions of schema and annotation type), as well as their presentations with views (templates applied on data to produce hypervideos) and queries. This model has been developed by the partners of the Cinelab project (2007-2008, funded by the french national research agency), and used afterwards in a number of projects and applications, including Advene (LIRIS) and Ligne de temps (IRI). @en
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The EduProgression ontology formalizes the educational progressions of the French educational system, making possible to represent the existing progressions in a standard formal model, searchable and understandable by machines (OWL). @en
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Version 2.0 of LexInfo Ontology, based on Lemon @en
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A Multilingual and Multicultural Ontology Representing Family Relationships. @en
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LinkedGeoData ontology has been derived from concepts defined by Open Street Map @en
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This ontology was used as example in the first OWL Recommendation (February 2004) @en
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The euBusinessGraph (`ebg:`) ontology represents companies, type/status/economic classification, addresses, identifiers, company officers (e.g., directors and CEOs), and dataset offerings. It uses `schema:domainIncludes/rangeIncludes` (which are polymorphic) to describe which properties are applicable to a class, rather than `rdfs:domain/range` (which are monomorphic) to prescribe what classes must be applied to each node using a property. We find that this enables more flexible reuse and combination of different ontologies. We reuse the following ontologies and nomenclatures, and extend them where appropriate with classes and properties: - W3C Org, W3C RegOrg (basic company data), - W3C Time (officer membership), - W3C Locn (addresses), - schema.org (domain/rangeIncludes and various properties) - DBpedia ontology (jurisdiction) - NGEO and Spatial (NUTS administrative divisions) - ADMS (identifiers), - FOAF, SIOC (blog posts), - RAMON, SKOS (NACE economic classifications and various nomenclatures), - VOID (dataset descriptions). This is only a reference. See more detail in the [EBG Semantic Model](https://docs.google.com/document/d/1dhMOTlIOC6dOK_jksJRX0CB-GIRoiYY6fWtCnZArUhU/edit) google document, which includes an informative description of classes and properties, gives examples and data provider rules, and provides more schema and instance diagrams. @en
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A vocabulary for European Calls for Tenders (in english, german, and french) @en
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This vocabulary defines temporal entities such as time intervals, their properties and relationships. @en
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Arpenteur ontology is dedicated to photogrammetry, archeology and oceanology communities in order to perform tasks such as image processing, photogrammetry and modelling. @en
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FAO's geopolitical ontology version 1.1 was populated with FAO, UN and internationally recognized data sources. @en
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NiceTag Ontology is an ontology which describes as generally as possible tags or rather tag actions understood as a speech acts occurring on the Web @en
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Appearances is an ontology that grew out of the need to record personal appearance details about individuals while taking into account errors of perception and translation between various diffferent standards. Originally it was meant to record physical caracteristics of Great War soldiers from their medical files, but it became evident that the resource was also useful for other purposes. @en
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The NORIA-O project is a data model for IT networks, events and operations information. The ontology is developed using web technologies (e.g. RDF, OWL, SKOS) and is intended as a structure for realizing an IT Service Management (ITSM) Knowledge Graph (KG) for Anomaly Detection (AD) and Risk Management 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: - [BBO](https://hal.archives-ouvertes.fr/hal-02365012/) 1.0.0 - [BOT](https://w3id.org/bot/) 0.3.2 - [DevOps-Infra](https://oeg-upm.github.io/devops-infra/) 1.0.0 - [FOLIO](https://github.com/IBCNServices/Folio-Ontology) 1.0.0 - [ORG](https://www.w3.org/TR/vocab-org/) 0.8 - [PEP](https://w3id.org/pep/) 1.1 - [SEAS](https://w3id.org/seas/) 1.1 - [SLOGERT](https://sepses.ifs.tuwien.ac.at/ns/log/index-en.html) 1.1.0 - [UCO](https://github.com/ucoProject/uco) Release-0.8.0 @en
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The Places Ontology is a simple lightweight ontology for describing places of geographic interest. @en