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LSC, the Linked Science Core Vocabulary, is a lightweight vocabulary providing terms to enable publishers and researchers to relate things in science to time, space, and themes. @en
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This vocabulary allows the semantic description of visual analytics applications. It is based on the RDF Data Cube Vocabulary and the Semanticscience Integrated Ontology. @en
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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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Primitive ontology for database to Semantic Web mapping which subsumes classes that represent mappings to explicit OWL constructs, such as OWL class, object property, data property, etc. Classes in this ontology are populated by individuals representing components of the database schema being mapped. @en
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The Measurement Ontology is an ontology in which measurements may be rendered @en
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The Delivery Context Ontology models the knowledge of the environment in which devices interact with the Web or other services @en
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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
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ML-Schema is a collaborative, community effort with a mission to develop, maintain, and promote standard schemas for data mining and machine learning algorithms, datasets, and experiments @en
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This ontology describes sensors, actuators and observations, and related concepts. It does not describe domain concepts, time, locations, etc. these are intended to be included from other ontologies via OWL imports. @en
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This document describes functions which transform HTTP representations, i.e., the actual literal payloads of HTTP messages. @en
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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
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An Ontology for representing EDIFACT Messages. @en
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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
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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
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The Cultural Event module models cultural events, i.e. events involving cultural properties. @en