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
This RDF document contains a library of data quality constraints represented as SPARQL query templates based on the SPARQL Inferencing Framework (SPIN). The data quality constraint templates are especially useful for the identification of data quality problems during data entry and for periodic quality checks during data usage. @en
Ontology Specialties describes all possible specialties (directions) in the RF, in which the UGNS they are composed, as well as information about their old codes / groups / names. @en
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
The interconnected data dictionary ontology maps the data model of the ISO 23386 for the describing, creating, and maintenance of properties in interconnected data dictionaries. @en
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
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