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  • An Ontology for representing EDIFACT Messages. @en
  • A small ontology to model supply networks (supply chains) from all industries through products that are interlinked based on derivational dependencies. @en
  • 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
  • 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
  • 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
  • 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
  • A vocabulary of particles used for observations in astronomy. This list started its existence as the controlled vocabulary for VODataService's vs:Waveband type; the machine-readable identifiers are in upper case for backwards compatibility. @en
  • 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
  • An Ontology for Consumer Electronics Products and Services @en
  • The Open NEE Configuration Model defines a Linked Data-based model for describing a configuration supported by a Named Entity Extraction (NEE) service. It is based on the model proposed in "Configuring Named Entity Extraction through Real-Time Exploitation of Linked Data" (http://dl.acm.org/citation.cfm?doid=2611040.2611085) for configuring such services, and allows a NEE service to describe and publish as Linked Data its entity mining capabilities, but also to be dynamically configured. @en
  • The Building Concrete Monitoring Ontology (BCOM) is defined for capturing information of concrete work, concrete curing and testing of concrete properties. Further Information on the development and usage of the Ontology can be found in the following publication: Liu et al. (2021): An ontology integrating as-built information for infrastructure asset management using BIM and semantic web. In: Proceedings of 2021 European Conference on Computing in Construction, Online eConference, URL: https://ec-3.org/publications/conferences/2021/paper/?id=167 @en
  • 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
  • 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
  • CiteDCAT-AP is an extension of the DCAT application profile for data portals in Europe (DCAT-AP) for describing resources documented by using the DataCite metadata schema - the de facto standard for data citation, and used across scientific disciplines. Its basic use case is to make research data searchable on general data portals, thereby bridging the gap between scientific and public sector information. For this purpose, CiteDCAT-AP provides an RDF vocabulary and the corresponding RDF syntax binding for the metadata elements defined in DataCite. @en