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An ontology for publishing descriptions of historical events as Linked Data, and for mapping between other event-related vocabularies and ontologies. @en
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LSC, the Linked Science Core Vocabulary, is a lightweight vocabulary providing terms to enable publishers and researchers to relate things in science to time, space, and themes. @en
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Vocabulary for datasets from the Netherlands' National Statistics Office @en
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This vocabulary allows the semantic description of visual analytics applications. It is based on the RDF Data Cube Vocabulary and the Semanticscience Integrated Ontology. @en
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Primitive ontology for database to Semantic Web mapping which subsumes classes that represent mappings to explicit OWL constructs, such as OWL class, object property, data property, etc. Classes in this ontology are populated by individuals representing components of the database schema being mapped. @en
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The Measurement Ontology is an ontology in which measurements may be rendered @en
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ML-Schema is a collaborative, community effort with a mission to develop, maintain, and promote standard schemas for data mining and machine learning algorithms, datasets, and experiments @en
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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
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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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This document describes functions which transform HTTP representations, i.e., the actual literal payloads of HTTP messages. @en
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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
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APCO is an ontology that allows the description of public procurement terms @en
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An Ontology for representing EDIFACT Messages. @en
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This ontology extends the SAREF ontology for the Smart City domain. This work has been developed in the context of the STF 534 (https://portal.etsi.org/STF/STFs/STFHomePages/STF534.aspx), which was established with the goal to create three SAREF extensions, one of them for the Smart City domain. @en
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The Crime Event Model is an ontology for the representation of crime events extracted from local newspapers. It could be employed for Crime Analysis purposes: extracting crime information from newspapers and enriching them with proper machine-readable semantics is a critical task to help law enforcement agencies at preventing crime, supporting criminal investigations and evaluating the action of law enforcement agencies themselves. The model is based on the fundamental 5W1H journalistic questions, that are Who?, What?, When?, Where?, Why? and How?. Another important requirement was the attempt to exploit existing knowledge graphs and ontologies such as the Simple Event Model (SEM) Ontology and the Schema.org data model for interoperability and interconnection. @en