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
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
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
Decision-making is a process that can result in some decision and decision is a situation of indicating one of the considered options. Decision Ontology provides means for precise distinguishing and distinct treatment of these two aspects. @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 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