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  • h2o - Ontology for conversion of ISO/TC 211
    http://def.seegrid.csiro.au/isotc211/iso19150/-2/2012/basic
    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
  • ext - OWL representation of ISO 19115 (Geographic Information - Metadata - Extent package)
    http://def.seegrid.csiro.au/isotc211/iso19115/2003/extent
    An OWL representation of parts of the Geographic Metadata model described in ISO 19115:2003 with Corrigendum 2006 - EX Package @en
  • sam - The Sampling Features Schema Vocabulary
    http://def.seegrid.csiro.au/isotc211/iso19156/2011/sampling
    An OWL representation of the Sampling Features Schema described in clauses 8-10 of ISO 19156:2011 Geographic Information - Observations and Measurements. @en
  • mexcore - MEX Core Vocabulary
    http://mex.aksw.org/mex-core
    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
  • mexalgo - MEX Algorithm Ontology
    http://mex.aksw.org/mex-algo
    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
  • mexperf - MEX Performance Ontology
    http://mex.aksw.org/mex-perf
    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
  • dbowl - Relational to Ontology Mapping Primitive
    http://ontology.cybershare.utep.edu/dbowl
    Primitive ontology for database to Semantic Web mapping which subsumes classes that represent mappings to explicit OWL constructs, such as OWL class, object property, data property, etc. Classes in this ontology are populated by individuals representing components of the database schema being mapped. @en
  • dbug - DOAP Bugs
    http://ontologi.es/doap-bugs#
    An extension of DOAP for the description of bugs @en
  • deps - DOAP Dependencies
    http://ontologi.es/doap-deps#
    An extension to DOAP for describing a project's requirements @en
  • semsur - The Semantic Survey Ontology (semsur)
    http://purl.org/SemSur/
    SemSur, the Semantic Survey Ontology, is a core ontology for describing individual research problems, approaches, implementations and evaluations in a structured, comparable way. @en
  • qu - Quantity Kinds and Units
    http://purl.oclc.org/NET/ssnx/qu/qu
    This ontology is partially based on the SysML QUDV (Quantities, Units, Dimensions and Values) proposed by a working group of the SysML 1.2 Revision Task Force (RTF), working in close coordination with the OMG MARTE specification group. In order to generalize its potential usage and alignment with other standardization efforts concerning quantities and units, the QU ontology has been further developed as a complement to the Agriculture Meteorology example showcasing the ontology developed by the W3C Semantic Sensor Networks incubator group (SSN-XG). @en
  • fiesta-priv - FIESTA-Priv Ontology
    http://purl.org/iot/ontology/fiesta-priv#
    FIESTA-Priv Ontology @en
  • iottaxolite - The IoTTaxonomy-lite Taxonomy
    http://purl.org/iot/vocab/iot-taxonomy-lite#
    The IoT-Taxonomy-lite is adapted from M3-lite taxonomy. This taxonomy is refactored and defines many other concepts such as subclasses of Feature-of-Interest and Quality-of-Observation. @en
  • fiesta-iot - FIESTA-IoT Ontology
    http://purl.org/iot/ontology/fiesta-iot
    The FIESTA-IoT ontology takes inspiration from the well-known Noy et al. methodology for reusing and interconnecting existing ontologies. To build the ontology, we leverage a number of core concepts from various mainstream ontologies and taxonomies, such as Semantic Sensor Network (SSN), M3-lite (a lite version of M3 ontology), WGS84, IoT-lite, Time, and DUL ontology. @en
  • qb - The data cube vocabulary
    http://purl.org/linked-data/cube
    This vocabulary allows multi-dimensional data, such as statistics, to be published in RDF. @en