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  • va - The Visual Analytics Vocabulary
    http://code-research.eu/ontology/visual-analytics
    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
  • geom - Ontology for geometry
    http://data.ign.fr/def/geometrie
    An ontology for describing the shape and the location of topographic entities @en
  • gm - OWL representation of ISO 19107 (Geographic Information)
    http://def.seegrid.csiro.au/isotc211/iso19107/2003/geometry
    An OWL representation of part of the model for geometry and space from ISO 19107:2003 Geographic Information - Spatial Schema @en
  • basic - OWL representation of ISO 19103 (Basic types package)
    http://def.seegrid.csiro.au/isotc211/iso19103/2005/basic
    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
  • ngeo - NeoGeo Geometry Ontology
    http://geovocab.org/geometry
    A vocabulary for specifying geographical regions in RDF @en
  • spatial - NeoGeo Spatial Ontology
    http://geovocab.org/spatial
    A vocabulary for describing topological relations between features @en
  • r4r - Relations for Reusing (R4R) Ontology
    http://guava.iis.sinica.edu.tw/r4r
    R4R is a light-weight ontology for representing general relationships of resource for publication and reusing. It asserts that a certain reusing context occurred and determined by its two basic relations, namely, isPackagedWith and isCitedBy. The isPackagedWith relation declares the resource is ready to be reused by incorporating License and Provenance information. The Cites relation is an exceptional to isCitedBy which occurs only two related objects cite each other at the same time. Five resource objects including article, data, code, provenance and license are major class concepts to represent in this ontology. The namespace for all R4R terms is http://guava.iis.sinica.edu.tw/r4r/ @en
  • dogont - Ontology Modeling for Intelligent Domotic Environments
    http://elite.polito.it/ontologies/dogont.owl
    The DogOnt ontology supports device/network independent description of houses, including both controllable and architectural elements. @en
  • eupont - EUPont: an ontology for End User Programming of the IoT
    http://elite.polito.it/ontologies/eupont.owl
    EUPont is an ontology to model high level rules for Internet of Things End User Programming (IoT-EUP). @en
  • op - Observable properties
    http://environment.data.gov.au/def/op
    A general purpose ontology for observable properties. The ontology supports description of both qualitative and quantitative properties. The allowed scale or units of measure may be specified. A property may be linked to substances-or-taxa and to features or realms, if they play a role in the definition. @en
  • ldvm - Vocabulary for Linked Data Visualization Model
    http://linked.opendata.cz/ontology/ldvm/
    Vocabulary for Linked Data Visualization Model (LDVM) serves for description and configuration of components and pipelines according to LDVM @en
  • lsc - Linked Science Core Vocabulary
    http://linkedscience.org/lsc/ns#
    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
  • psh - Probabilistic SHACL Validation
    http://ns.inria.fr/probabilistic-shacl/
    An OWL vocabulary to include and exploit probabilistic information in SHACL validation reports @en
  • nrv - Normative Requirements Vocabulary
    http://ns.inria.fr/nrv
    An OWL vocabulary for describing normative requirements. @en
  • opmo - Open Provenance Model
    http://openprovenance.org/model/opmo
    The Open Provenance Model is a model of provenance that is designed to meet the following requirements: (1) To allow provenance information to be exchanged between systems, by means of a compatibility layer based on a shared provenance model. (2) To allow developers to build and share tools that operate on such a provenance model. (3) To define provenance in a precise, technology-agnostic manner. (4) To support a digital representation of provenance for any 'thing', whether produced by computer systems or not. (5) To allow multiple levels of description to coexist. (6) To define a core set of rules that identify the valid inferences that can be made on provenance representation. @en