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The QUDT, or 'Quantity, Unit, Dimension and Type' collection of ontologies define the base classes properties, and restrictions used for modeling physical quantities, units of measure, and their dimensions in various measurement systems. @en
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A metadata vocabulary for documenting research and survey data @en
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Ontology with classes and properties used for demography, mostly in the census of the population @en
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An ontology to describe experiments, evaluations and their relation. @en
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Elementary Multiperspective Material Ontology (EMMO) EMMO is a multidisciplinary effort to develop a standard representational framework (the ontology) based on current materials modelling knowledge, including physical sciences, analytical philosophy and information and communication technologies. It provides the connection between the physical world, materials characterisation world and materials modelling world. @en
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CHAMEO is a domain ontology designed to model the common aspects across the different characterisation techniques and methodologies. @en
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A simple ontology which implements the Parameter Usage Vocabulary semantic model, as described at https://github.com/nvs-vocabs/P01 @en
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PROV extension for linking Plans and parts of plans to their respective executions. @en
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An ontology to model food donation logistics. @en
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A vocabulary to represent the AutomationML Standard - IEC 62714 @en
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A vocabulary which represents the Reference Architecture Model for Industry 4.0 (RAMI), including the concept of the Administration Shell I4.0 Component. @en
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A vocabulary to describe the relation between standards in use on the Industry 4.0, and related concepts @en
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The ICON ontology deals with high granularity art interpretation. It was developed by conceptualizing Panofsky's theory of levels of interpretation, therefore artworks can be described according to Pre-iconographical, Iconographical and Iconological information. @en
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The Ishikawa ontology aims to provide a data and view model to manage data encoded in Ishikawa diagrams which are also known as fishbone or cause and effect diagram (CED). Ishikawa diagrams result from (iterative) workshops. Thus, the ontology includes the basic modelling of workshops to create Ishikawa diagrams. @en
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The Level of Information Need (LOIN) Ontology is defined for specifying information requirements for delivery of data in a buildings' life cycle. The LOIN ontology is based on the standard BS EN 17412-1 (2020). Furthermore, it is extended with vocabulary for connecing Information Delivery Specifications (IDS) and Information containers for linked document delivery (ICDD) as per ISO 21597-1 (2020). @en