79
results
-
Defines concepts related to the structure of the US National Airspace System (NAS) @en
-
Defines aircraft models, aircraft systems / subsystems, and aircraft characteristics @en
-
This document specifies a vocabulary for describing an IBIS (issue-based information system). @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 development of the SAREF4GRID ontology has been partially funded by the IA4TES project (MIA.2021.M04.0008), funded by the Spanish Ministry of Economic Affairs and Digital Transformation and by the NextGenerationEU program @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
-
GConsent provides concepts and relationships for defining consent and its associated information or metadata with a view towards GDPR compliance. It is the outcome of an analysis of consent and requirements associated with obtaining, using, and changes in consent as per the GDPR. The ontology also provides an approach to using its terms in various scenarios and use-cases (see more information in the documentation) which is intended to assist in its adoption. @en
-
The General Data Protection Regulation (GDPR) is comprised of several articles, each with points that refer to specific concepts. The general convention of referring to these points and concepts is to quote the specific article or point using a human-readable reference. This ontology provides a way to refer to the points within the GDPR using the EurLex ontology published by the European Publication Office. It also defines the concepts defined, mentioned, and requried by the GDPR using the Simple Knowledge Organization System (SKOS) ontology. @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 Core module represents general-purpose concepts orthogonal to the whole network, which are imported by all other ontology modules (e.g. part-whole relation, classification). @en
-
The Context Description module includes models for the context of a cultural property, in a broad sense: agents (e.g.: author, collector, copyright holder), objects (e.g.: inventories, bibliography, protective measures, other cultural properties, collections etc.), activities (e.g.: surveys, conservation interventions), situations (e.g.: commission, coin issuance, estimate, legal situation) related, involved or involving the cultural property. Thus it represents attributes that do not result from a measurement of features in a cultural property, but are associated with it. @en
-
The Denotative Description module encodes the characteristics of a cultural property, as detectable and/or detected during the cataloguing process and measurable according to a reference system. Examples include measurements e.g. length, constituting materials e.g. clay, employed techniques e.g. melting, conservation status e.g. good, decent, bad. 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/descriptionandsituation.owl - http://www.ontologydesignpatterns.org/cp/owl/situation.owl @en
-
Extension to the Data Privacy Vocabulary (DPV) providing additional categories of personal data @en
-
A FAIR-compliant metadata vocabulary (MV), the Library Transaction Ontology (LTO), is designed and developed for representing and managing library transaction data (LTD), including circulation, interlibrary loan, hold requests, and fiscal information. Our investigation revealed that despite significant focus on bibliographic and authority data, no standardized vocabulary exists for LTD, resulting in data loss, mapping errors, and interoperability challenges during system migration and integration. LTO supports machine processing and automated reasoning for data-driven decision making. Additionally, it supports interoperability across heterogeneous library platforms by providing mappings for the circulation metadata of multiple Library Management Systems (LMS), including Koha, Virtua, Evergreen, SOUL, etc. It is also compliant with the Library of Congress's (LOC) BIBFRAME model and extends the bibliographic Linked Data (LD) framework to support the standardized representation of library transaction LD. LTO?s elements were validated through expert evaluation by LIS professionals, and its effectiveness in information processing and retrieval was successfully assessed. @en