52
results
  • FOAF is a project devoted to linking people and information using the Web. Regardless of whether information is in people's heads, in physical or digital documents, or in the form of factual data, it can be linked. @en
  • This document specifies a vocabulary for describing an IBIS (issue-based information system). @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
  • GDPRov is an OWL2 ontology to express provenance metadata of consent and data lifecycles towards documenting compliance for GDPR. @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
  • A vocabulary to represent relations that should be more transparent, usually between powerfull people or institutions @en
  • A vocabulary to describe a person's profile and history @en
  • The ontology has been developed in the framework of the Dem@Care project for representing the experimentation protocol towards diagnostic support and assessment of Dementia in a controlled environment. The aim of the protocol is to provide a brief overview of their health status of the participants during consultation (cognition, behaviours and function), and to correlate the system (sensor) data with the data collected using typical dementia care assessment tools. @en
  • This ontology describes a person character as a vector of demographic traits, each dimension refers to a concept contained within a specific taxonomy or to an instance of a wikidata item. @en
  • The Data Privacy Vocabulary (DPV) provides terms (classes and properties) to represent information about processing of personal data, for example - purposes, processing operations, personal data, technical and organisational measures. @en
  • Extension to the Data Privacy Vocabulary (DPV) providing additional categories of personal data @en
  • The ontology of agent relationships, AgRelOn, defines relations of persons to other persons and to organisations @en
  • The Cochrane Core ontology describes the entities and concepts that exist in the domain of evidence based healthcare. It is used for the construction of the Cochrane Linked Data Vocabulary containing some 400k terms including Interventions (Drugs, Procedures etc), Populations (Age, Sex, Condition), and clinical Outcomes. @en
  • The PICO ontology provides a machine accessible version of the PICO framework. It essentially provides a model for describing evidence in a consistent way. The model allows the specifying of complex populations, detailed interventions and their comparisons as well as the outcomes considered. The PICO ontology was originally designed to model the questions asked and answered in Cochrane's systematic reviews. As a leader in the field of evidence based healthcare Cochrane uses the PICO model when framing and publishing evidence based questions. The PICO model is widely adopted for describing healthcare evidence, furthermore is equally applicable in other evidence-based domains. It essentially provides a model for describing evidence in a consistent way. @en
  • The Ontology for Biomedical Investigations (OBI) is build in a collaborative, international effort and will serve as a resource for annotating biomedical investigations, including the study design, protocols and instrumentation used, the data generated and the types of analysis performed on the data. This ontology arose from the Functional Genomics Investigation Ontology (FuGO) and will contain both terms that are common to all biomedical investigations, including functional genomics investigations and those that are more domain specific. @en