• Facets (new session)
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  • Rule: ActivityStreamsMapasEquivalentb3sb3sifpdbprdf-labelfacetshttp://dbpedia.org/resource/inference/rules/dbpedia#http://dbpedia.org/resource/inference/rules/opencyc#http://dbpedia.org/resource/inference/rules/umbel#http://dbpedia.org/resource/inference/rules/yago#http://dbpedia.org/schema/property_rules#http://www.ontologyportal.org/inference/rules/SUMO#http://www.ontologyportal.org/inference/rules/WordNet#http://www.w3.org/2002/07/owl#ldpoplwebskos-transurn:det:rdf:labelvirtrdf-labelvirtrdf-urlNone
    
  • Inverse Functional Properties: Disabled (fastest) Apply to subjects only Apply to objects only Apply to both subjects and objects
  • "Same As": Disabled (fastest) Apply to subjects only Apply to objects only Apply to both subjects and objects (recommended) Apply to subjects, objects and predicates (not recommended on big datasets) Apply to predicates only (special use cases only)

About: OpenWebGlobe     Goto   Sponge   NotDistinct   Permalink

An Entity of Type : yago:Software106566077, within Data Space : dbpedia.org associated with source document(s)

Type: Thingsoftwareschema:CreativeWorkworkwikidata:Q386724Softwareyago:Abstraction100002137yago:Code106355894yago:CodingSystem106353757yago:Communication100033020yago:Writing106359877yago:WrittenCommunication106349220Bandyago:Software106566077 New Facet based on Instances of this Class

OpenWebGlobe was a project and technology for processing and interactively visualizing vast volumes of geospatial data in a 3D virtual globe, even the forks on GitHub are rather dead [1].The OpenWebGlobe virtual globe can have several data categories like image data, elevation data, points of interest, vector data, and 3D objects. Before streaming such massive and complex data over the internet, this data must be pre-processed. Such pre-processing usually comprises a transformation from a local to a global reference system, creation of pyramid layers or levels of detail (LOD), tiling of the data, and optionally compression and encryption. Recently, these algorithms were ported to high performance compute cluster using OpenMP and MPI and are also released as open-source. Because data sets a