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  • The ECLAP vocabulary provide classes and properties for the description of multimedia content related with performing arts. @en
  • A vocabulary, or music ontology, to describe classical music and performances. Classes (categories) for musical works, events, instruments and performers, as well as related properties are defined. Make sure to distinguish musical works (e.g. Opera) from performance events (Opera_Event), or works (String_Quartette) from performer (StringQuartetEnsemble in this vocab), whose natural language terms are used interchangeblly. The present version experiments more precise model to describe a musical work, its representations (performances, scores, etc) and a musical event to present a representation (a concert). Includes 30 keys as individuals. @en
  • A pattern to represent contexts or situations, and the things that are contextualized. @en
  • A generic pattern usable for all situations that require a temporal indexing. @en
  • TISC, the Open Time and Space Core Vocabulary, is a lightweight spatiotemporal vocabulary aiming to provide spatial and temporal terms such as "happensAt", "locatedAt", "rightOf" to enable practitioners to relate their data to time and space. @en
  • Designed with the goals to describe and encode the core dramatic qualities and to serve as a knowledge base underlying a number of applications, Drammar is a comprehensive ontology of drama, realized through a collaboration of computer scientists and drama scholars. It makes the knowledge about drama available as a vocabulary for the linked interchange of drama encodings and readily usable by automatic reasoners. By avoinding references to style and artistic qualities Drammar aims at representing the elements shared by different, cross-media manifestations of drama, the so–called intangible elements of drama as an intangible cultural heritage form. @en
  • The SeaLiT Ontology is a formal ontology intended to facilitate the integration, mediation and interchange of heterogeneous information related to maritime history. It aims at providing the semantic definitions needed to transform disparate, localised information sources of maritime history into a coherent global resource. It also serves as a common language for domain experts and IT developers to formulate requirements and to agree on system functionalities with respect to the correct handling of historical information. The ontology uses and extends the CIDOC Conceptual Reference Model (ISO 21127:2014), in particular version 7.1.1, as a general ontology of human activity, things and events happening in space and time. @en
  • The Delivery Context Ontology models the knowledge of the environment in which devices interact with the Web or other services @en
  • The Ontology for Media Resources 1.0 describes a core vocabulary of properties and a set of mappings between different metadata formats of media resources hat describe media resources published on the Web (as opposed to local archives, museums, or other non-web related and non-shared collections of media resources). @en
  • ISTEX is a platform that aims to provide the entire French higher education and research community with an online access to retrospective collections of scientific literature in all disciplines. This unparalleled reservoir of multidisciplinary resources is complemented by a significant number of value-added services that can be used to optimise operations through content discovery and interactive valuation tools. @en
  • This ontology models personalized tourist experiences by representing cities, points of interest, events, accommodations, restaurants, transportation, and their relationships. This ontology is part of a university project. @en
  • The ontology describes the main concepts in the field of education and the connections between them. The current version emphasizes the details of the study material, learning outcomes and the curriculum. @en
  • The Crime Event Model is an ontology for the representation of crime events extracted from local newspapers. It could be employed for Crime Analysis purposes: extracting crime information from newspapers and enriching them with proper machine-readable semantics is a critical task to help law enforcement agencies at preventing crime, supporting criminal investigations and evaluating the action of law enforcement agencies themselves. The model is based on the fundamental 5W1H journalistic questions, that are Who?, What?, When?, Where?, Why? and How?. Another important requirement was the attempt to exploit existing knowledge graphs and ontologies such as the Simple Event Model (SEM) Ontology and the Schema.org data model for interoperability and interconnection. @en
  • The notion of territory plays a major role in human and social sciences. In an historical context, most approaches are irrelevant as they rely on geometric data, which is not available. In order to represent historical territories,we conceived the HHT ontology (Hierarchical Historical Territory) to represent hierarchical historical territorial divisions, without having to know their geometry. This approach relies on a notion of building blocks to replace polygonal geometry @en
  • The Cultural Event module models cultural events, i.e. events involving cultural properties. @en