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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
  • GDPRov is an OWL2 ontology to express provenance metadata of consent and data lifecycles towards documenting compliance for GDPR. @en
  • AIRO represents AI risk concepts and relations based on the AI Act draft and ISO 31000 standard series. @en
  • The module Location models information related to the localization and georeferencing of a cultural property. In this module are used as template the following Ontology Design Patterns: - http://www.ontologydesignpatterns.org/cp/owl/collectionentity.owl - http://www.ontologydesignpatterns.org/cp/owl/classification.owl - http://www.ontologydesignpatterns.org/cp/owl/place.owl - http://www.ontologydesignpatterns.org/cp/owl/timeindexedsituation.owl - http://www.ontologydesignpatterns.org/cp/owl/situation.owl @en
  • Ontology that defines the topology of damages in constructions. @en
  • Quality, architecture, and process are considered the keystones of software engineering. ISO defines them in three separate standards. However, their interaction has been poorly studied, so far. The SQuAP model (Software Quality, Architecture, Process) describes twenty-eight main factors that impact on software quality in banking systems, and each factor is described as a relation among some characteristics from the three ISO standards. Hence, SQuAP makes such relations emerge rigorously, although informally. SQaAP-Ont is an OWL ontology that formalises those relations in order to represent and reason via Linked Data about software engineering in a three-dimensional model consisting of quality, architecture, and process characteristics. @en
  • A vocabulary specifying concepts and structures needed to represent different data cubes needed for the Smart Readiness Indicator. @en
  • The Gouda Time Machine Ontology describes the geo-temporal classes and properties used within the Gouda Time Machine. @en
  • Ontology defining concepts for Geocoding of addresses. It is based on the geocoding used in the Global Legal Entity Identifier Foundation (GLEIF) Golden Copy Data, but is more broadly applicable. @en
  • Ontology defining generic concepts for reuse by other Global Legal Entity Identifier Foundation (GLEIF) ontologies. It defines generic classes for (legal) Entities and their relationships and statuses; and generic properties for different types of name and address. It makes use of the OMG Languages Countries and Codes (LCC) ontology (based on the ISO 3166 standard) for country and region information. @en