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ei2a - Aragon Interoperable Information Structure Ontology EI2A https://opendata.aragon.es/def/ei2a/ei2a.owl 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 -
ci - A Content Inventory Vocabulary https://privatealpha.com/ontology/content-inventory/1# This vocabulary defines a number of concepts peculiar to content strategy which are not accounted for by other vocabularies. @en -
wty - Verisav Warranty & Contracts Vocabulary https://ns.verisav.fr/wty# Vocabulary for machine-readable warranties and contracts, enabling complete automation of payment decisions and coverage assessment in after-sales service. @en -
psn - Product Supply Network Vocabulary https://purl.org/psn/vocab# A small ontology to model supply networks (supply chains) from all industries through products that are interlinked based on derivational dependencies. @en -
apco - African Public Contract Ontology https://purl.org/cm/onto/apco APCO is an ontology that allows the description of public procurement terms @en -
saref - SAREF: the Smart Appliances REFerence ontology https://saref.etsi.org/core/ The Smart Appliances REFerence (SAREF) ontology is a shared model of consensus that facilitates the matching of existing assets (standards/protocols/datamodels/etc.) in the smart appliances domain. The SAREF ontology provides building blocks that allow separation and recombination of different parts of the ontology depending on specific needs. @en -
s4city - SAREF extension for Smart City https://saref.etsi.org/saref4city/ 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 -
s4inma - SAREF4INMA: an extension of SAREF for the industry and manufacturing domain https://saref.etsi.org/saref4inma/ SAREF4INMA is an extension of SAREF for the industry and manufacturing domain. SAREF4INMA focuses on extending SAREF for the industry and manufacturing domain to solve the lack of interoperability between various types of production equipment that produce items in a factory and, once outside the factory, between different organizations in the value chain to uniquely track back the produced items to the corresponding production equipment, batches, material and precise time in which they were manufactured. SAREF4INMA is specified and published by ETSI in the TS 103 410-5 associated to this ontology file. SAREF4INMA was created to be aligned with related initiatives in the smart industry and manufacturing domain in terms of modelling and standardization, such as the Reference Architecture Model for Industry 4.0 (RAMI), which combines several standards used by the various national initiatives in Europe that support digitalization in manufacturing. The full list of use cases, standards and requirements that guided the creation of SAREF4INMA are described in the associated ETSI TR 103 507. @en -
gdprt - GDPR text EXTensions https://w3id.org/GDPRtEXT 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 -
IIoT - Ontology for Industrial Internet of Things systems https://w3id.org/IIoT The Internet of Things taxonomy is extended with semantic ontologies for IoT layers, containing classes, properties, individuals, and rules specific to IoT technologies, tools, and applications @en -
gsn - OntoGSN https://w3id.org/OntoGSN/ontology OntoGSN is an ontology for managing assurance cases in the Goal Structuring Notation (GSN). The goal of the ontology is to help users in linking the elements of their cases - claims and evidence - with the internationalized resource identifiers (IRIs) of represented concepts, events and data, and in evaluating the validity of their argument. @en -
amv - AMV:Algorithm Metadata Vocabulary https://w3id.org/amv Metadata vocabularies are used in various domains of study. It provides an in-depth description of the resources. In this work, we develop Algorithm Metadata Vocabulary (AMV), a vocabulary for capturing and storing the metadata about the algorithms (a procedure or a set of rules that is followed step-by-step to solve a problem, especially by a computer). The snag faced by the researchers in the current time is the failure of getting relevant results when searching for algorithms in any search engine. AMV is represented as a semantic model and produced OWL file, which can be directly used by anyone interested to create and publish algorithm metadata as a knowledge graph, or to provide metadata service through SPARQL endpoint. To design the vocabulary, we propose a well-defined methodology, which considers real issues faced by the algorithm users and the practitioners. The evaluation shows a promising result. @en -
cmd - Compound Measure Description https://w3id.org/cmd# This document is a vocabulary to describe compound measures, i.e. measures with several metric or item that are organized with serveral dimensions. The description of such a measure relies on a Tree-Structure of Requirement (TSoR): a set of requirements structured hierarchicaly with analysis element. A TSoR represents the main measure. Several information may be added to explicitely indicate how the overall score on the measure should be calculated based on the hierarchy, relative importance of the node of the hierarchy and an aggregation function. The measure can be described completely and unambiguously from the organisation to the requirements and the implementation. @en -
cdc - CDC: Construction Dataset Context ontology https://w3id.org/cdc The Construction Dataset Context (CDC) ontology is an extension of DCAT v2.0, a W3C Recommendation ontology for describing (RDF and non-RDF) datasets published on the Web. Using this extension, it becomes possible to describe a context for construction-related datasets that are being distributed using Web technology as well as datasets that are not shared outside an organization such as local copies, work in progress and other datasets that remain internal. This dataset metadata encompasses the temporal context (period or snapshot), the type of content of the dataset (as-built, design, etc.) and relations between contextualized datasets (previous as-built, requirements related to a design, etc.). In addition, this DCAT extension also provides terminology for managing dataset distributions that are scoped to a certain (named or default) graph of an RDF file or quadstore. @en -
bto - BOT: Building Topology Ontology https://w3id.org/bot The Building Topology Ontology (BOT) is a simple ontology defining the core concepts of a building. It is a simple, easy to extend ontology for the construction industry to document and exchange building data on the web. Changes since version 0.2.0 of the ontology are documented in: https://w3id.org/bot/bot.html#changes The version 0.2.0 of the ontology is documented in: Mads Holten Rasmussen, Pieter Pauwels, Maxime Lefrançois, Georg Ferdinand Schneider, Christian Anker Hviid and Jan Karlshøj (2017) Recent changes in the Building Topology Ontology, 5th Linked Data in Architecture and Construction Workshop (LDAC2017), November 13-15, 2017, Dijon, France, https://www.researchgate.net/publication/320631574_Recent_changes_in_the_Building_Topology_Ontology The initial version 0.1.0 of the ontology was documented in: Mads Holten Rasmussen, Pieter Pauwels, Christian Anker Hviid and Jan Karlshøj (2017) Proposing a Central AEC Ontology That Allows for Domain Specific Extensions, Lean and Computing in Construction Congress (LC3): Volume I – Proceedings of the Joint Conference on Computing in Construction (JC3), July 4-7, 2017, Heraklion, Greece, pp. 237-244 https://doi.org/10.24928/JC3-2017/0153 @en