MEX is an RDF vocabulary designed to facilitate interoperability between published machine learning experiments results on the Web. The mex-algo layer represents the algorithm information existing into a basic machine learning experiment. @en
MEX is an RDF vocabulary designed to facilitate interoperability between published machine learning experiments results on the Web. The mex-core layer represents the core information gathered from a basic machine learning experiment design. @en
MEX is an RDF vocabulary designed to facilitate interoperability between published machine learning experiments results on the Web. The mex-perf layer is the 3rd level of the MEX for representing the machine learning algorithm's performances. @en
The EduProgression ontology formalizes the educational progressions of the French educational system, making possible to represent the existing progressions in a standard formal model, searchable and understandable by machines (OWL). @en
The Core Ontology is a formal model providing definitions for the key concepts of interest to content publishing at Macmillan Science and Education. @en
Press.net Asset Ontology describes news assets (text, images, video, data, etc), the relationships between them and how assets can be classified and semantically annotated. @en
Press.net Stuff Ontology models real world entities. There are two kinds of stuff: tangibles and intangibles. Tangible stuff includes persons, locations and organizations. Intangibles are abstract concepts such as smoking, feminism or love. @en
An OWL representation of (some of) the basic types described in ISO 19103:2005, required as primitives in other ontologies based on ISO 19100 series standards @en
This ontology establishes classes corresponding to stereotypes used in ISO-conformant models, as used in the rules for conversion of the ISO TC 211 Harmonized Model from the UML to OWL representations @en