• Facets (new session)
• Description
• Metadata
• Settings
  • 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: Listen to Wikipedia     Goto   Sponge   NotDistinct   Permalink

An Entity of Type : wikidata:Q7397, within Data Space : dbpedia.org associated with source document(s)

Type: Thingsoftwareschema:CreativeWorkworkwikidata:Q386724Software New Facet based on Instances of this Class

Listen to Wikipedia, also known as L2W or Hatnote: Listen To Wikipedia, is a multimedia visualizer developed by Mahmoud Hashemi and Stephen LaPorte which translates recent Wikipedia edits into a display of visuals and sounds. The open source software application creates a real-time statistical graphic with sound from contributions to Wikipedia from around the world. To accomplish this, L2W uses the graphics library D3.js. The concept of Listen to Wikipedia is based on , originally known as Listen to Bitcoin, an application by Maximillian Laumeister.