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Ontology for Certificates and crypto stuff. @en
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This document describes the RDFS vocabulary description used in the Metadata Vocabulary for Tabular Data along with the default JSON-LD Context. @en
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This vocabulary defines terms used in SHACL, the W3C Shapes Constraint Language. @en
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The Open Annotation Core Data Model specifies an interoperable framework for creating associations between related resources, annotations, using a methodology that conforms to the Architecture of the World Wide Web. This ontology is a non-normative OWL formalization of the textual OA specification at http://www.openannotation.org/spec/core/20130208/index.html @en
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A model for the representation of lexical information relative to ontologies. Core module. @en
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A model for the representation of lexical information relative to ontologies. Syntax and semantics module. @en
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Web Of Trust (wot) RDF vocabulary, described using W3C RDF Schema and the Web Ontology Language. @en
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Extensions to SKOS and other standard vocabularies used by the German National Library of Economics (ZBW) @en
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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
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The initiative Aragón Open Data was initiated by agreement of 17 of July of 2012 of the Government of Aragon. Under the same was ordered the start of the project to open public data and on February 6, 2013 was implemented through the Portal <a href="http://opendata.aragon.es/"> opendata.aragon.es </a>. Throughout this time there have been numerous works to achieve automation in the publication of information to ensure that third parties can reuse it in the best way. Given the volume of data that begins to exist, within the line of work of automation in information management, all those elements that help in the improvement of the <b> structuring of information </b> and the <b> standardization of the data </b> contained in the databases are beginning to have a special relevance. Based on this, within the General Directorate of Electronic Administration and Information Society, the idea arises of generating a set of technical and legal rules that allow to deepen in that standardization and that lead to think in the creation of the Interoperable Information Scheme Of Aragon (E2IA). The E2IA thus emerges as the framework in which the open data and in general the information of the Government of Aragon can begin to be automated in a much more profound way. The E2IA has to have a number of technical, organizational and legal elements that need to be developed. For this reason, the Technological Institute of Aragon (ITAINNOVA) has been entrusted with carrying out actions consisting in identifying, studying and analyzing current research trends and technological development in relation to ontologies and dictionaries of data interoperability, defining the ontological proposal, performing The necessary tests to validate the ontological proposal and generate the text and web versions of the ontology. @en
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GDPRov is an OWL2 ontology to express provenance metadata of consent and data lifecycles towards documenting compliance for GDPR. @en
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AIRO represents AI risk concepts and relations based on the AI Act draft and ISO 31000 standard series. @en
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Data Specification Vocabulary (DSV) is a vocabulary for describing semantic data specifications, namely vocabularies and application profiles. @en
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An ontology for describing changes between OWL ontology versions @en
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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