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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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A vocabulary to represent relations that should be more transparent, usually between powerfull people or institutions @en
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Version 2.0 of LexInfo Ontology, based on Lemon @en
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A vocabulary to describe signs in a semiotic approach @en
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An ontology of topics as used in thesauri, subject directories, etc. @en
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The Data Knowledge Vocabulary allows for a comprehensive description of data assets and enterprise data management. It covers a business data dictionary, data quality management, data governance, the technical infrastructure and many other aspects of enterprise data management. The vocabulary represents a linked data implementation of the Data Knowledge Model which resulted from extensive applied research. @en
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An ontology that let users define relationships between Tag objects and URIs of Semantic Web resources @en
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An ontology for describing changes between OWL ontology versions @en
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This ontology is a composition of some content design patterns for the semiotic triangle. Its structure is extracted from DOLCE-Ultralite (DOLCE+c.DnS), but it uses a different terminology, @en
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An ontology for aligning existing linguistic ontologies, and for describing the research objects of NLP. @en
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Common Tags are references to unique, well-defined concepts, complete with metadata and their own URLs. @en
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The euBusinessGraph (`ebg:`) ontology represents companies, type/status/economic classification, addresses, identifiers, company officers (e.g., directors and CEOs), and dataset offerings. It uses `schema:domainIncludes/rangeIncludes` (which are polymorphic) to describe which properties are applicable to a class, rather than `rdfs:domain/range` (which are monomorphic) to prescribe what classes must be applied to each node using a property. We find that this enables more flexible reuse and combination of different ontologies. We reuse the following ontologies and nomenclatures, and extend them where appropriate with classes and properties: - W3C Org, W3C RegOrg (basic company data), - W3C Time (officer membership), - W3C Locn (addresses), - schema.org (domain/rangeIncludes and various properties) - DBpedia ontology (jurisdiction) - NGEO and Spatial (NUTS administrative divisions) - ADMS (identifiers), - FOAF, SIOC (blog posts), - RAMON, SKOS (NACE economic classifications and various nomenclatures), - VOID (dataset descriptions). This is only a reference. See more detail in the [EBG Semantic Model](https://docs.google.com/document/d/1dhMOTlIOC6dOK_jksJRX0CB-GIRoiYY6fWtCnZArUhU/edit) google document, which includes an informative description of classes and properties, gives examples and data provider rules, and provides more schema and instance diagrams. @en
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The NLP Interchange Format (NIF) is an RDF/OWL-based format that aims to achieve interoperability between Natural Language Processing (NLP) tools, language resources and annotations. @en
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The FrameNet module of the PreMOn ontology extends the core module for representing concepts specific to FrameNet. The modeling is based on the [FrameNet II: Extended Theory and Practice](https://framenet2.icsi.berkeley.edu/docs/r1.5/book.pdf) book. @en