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results
  • Vocabulary for describing organizational structures, specializable to a broad variety of types of organization. @en
  • The namespace name http://www.w3.org/ns/prov# is intended for use with the PROV family of documents that support the interchange of provenance on the web. @en
  • A vocabulary for describing SPARQL services made available via the SPARQL 1.1 Protocol for RDF. These descriptions provide a mechanism by which a client or end user can discover information about the SPARQL service such as supported extension functions and details about the available dataset. @en
  • This ontology describes sensors, actuators and observations, and related concepts. It does not describe domain concepts, time, locations, etc. these are intended to be included from other ontologies via OWL imports. @en
  • Web Of Trust (wot) RDF vocabulary, described using W3C RDF Schema and the Web Ontology Language. @en
  • The ontology is aimed at the support of research groups in the field of Business Modeling and Knowledge Engineering (BMaKE) in their collaborative work for qualitatively analyzing scholarly papers as well as sharing the results of that analyses and judgements. @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 FAIR Assessment Ontology is designed to model the process and outcomes of evaluating digital objects according to the FAIR principles. It captures FAIR assessments as provenance-aware activities, linking evaluated resources to detailed results for each FAIR sub-principle. Each assessment can include multiple sub-principle results, associated evidence, quantitative scores, and test outcomes (e.g., pass, fail, indeterminate). The ontology also models the computational aspects of FAIR evaluation, including scoring functions, calculation algorithms, and aggregation methods used to derive higher-level scores. The ontology is aligned with the FAIR Vocabulary (https://w3id.org/fair/principles/terms/) for the definition of principles and sub-principles, and reuses established standards such as PROV-O for provenance and SKOS for controlled vocabularies. This ensures interoperability with existing FAIR tools and supports integration into automated FAIR assessment pipelines. @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