@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .
@prefix owl: <http://www.w3.org/2002/07/owl#> .
@prefix constant: <http://qudt.org/vocab/constant/> .
@prefix dc: <http://purl.org/dc/elements/1.1/> .
@prefix dcterms: <http://purl.org/dc/terms/> .
@prefix prov: <http://www.w3.org/ns/prov#> .
@prefix qkdv: <http://qudt.org/vocab/dimensionvector/> .
@prefix quantitykind: <http://qudt.org/vocab/quantitykind/> .
@prefix qudt: <http://qudt.org/schema/qudt/> .
@prefix si-quantity: <https://si-digital-framework.org/quantities/> .
@prefix skos: <http://www.w3.org/2004/02/skos/core#> .
@prefix unit: <http://qudt.org/vocab/unit/> .
@prefix vaem: <http://www.linkedmodel.org/schema/vaem#> .
@prefix voag: <http://voag.linkedmodel.org/schema/voag#> .

quantitykind:InformationEntropy
  a qudt:QuantityKind ;
  dcterms:description """Information Entropy is a concept from information theory. It tells how much information there is in an
    event. In general, the more uncertain or random the event is, the more information it will contain. The concept of information
    entropy was created by a mathematician. He was named Claude Elwood Shannon. It has applications in many areas, including
    lossless data compression, statistical inference, cryptography and recently in other disciplines as biology, physics or
    machine learning.
  """^^qudt:LatexString ;
  qudt:applicableUnit unit:BAN ;
  qudt:applicableUnit unit:BIT ;
  qudt:applicableUnit unit:BYTE ;
  qudt:applicableUnit unit:ERLANG ;
  qudt:applicableUnit unit:ExaBIT ;
  qudt:applicableUnit unit:ExaBYTE ;
  qudt:applicableUnit unit:ExbiBIT ;
  qudt:applicableUnit unit:ExbiBYTE ;
  qudt:applicableUnit unit:GibiBYTE ;
  qudt:applicableUnit unit:GigaBYTE ;
  qudt:applicableUnit unit:HART ;
  qudt:applicableUnit unit:KibiBYTE ;
  qudt:applicableUnit unit:KiloBYTE ;
  qudt:applicableUnit unit:MebiBYTE ;
  qudt:applicableUnit unit:MegaBYTE ;
  qudt:applicableUnit unit:NAT ;
  qudt:applicableUnit unit:PebiBIT ;
  qudt:applicableUnit unit:PebiBYTE ;
  qudt:applicableUnit unit:PetaBYTE ;
  qudt:applicableUnit unit:SHANNON ;
  qudt:applicableUnit unit:TebiBIT ;
  qudt:applicableUnit unit:TebiBYTE ;
  qudt:applicableUnit unit:TeraBYTE ;
  qudt:hasDimensionVector qkdv:A0E0L0I0M0H0T0D1 ;
  qudt:informativeReference "http://simple.wikipedia.org/wiki/Information_entropy"^^xsd:anyURI ;
  qudt:organizedUnder quantitykind:Dimensionless ;
  qudt:plainTextDescription """Information Entropy is a concept from information theory. It tells how much information there is in
    an event. In general, the more uncertain or random the event is, the more information it will contain. The concept of
    information entropy was created by a mathematician. He was named Claude Elwood Shannon. It has applications in many areas,
    including lossless data compression, statistical inference, cryptography and recently in other disciplines as biology, physics
    or machine learning.
  """ ;
  qudt:wikidataMatch <http://www.wikidata.org/entity/Q204570> ;
  rdfs:comment "Applicable units are those of quantitykind:InformationEntropy" ;
  rdfs:isDefinedBy <http://qudt.org/3.4.0/vocab/quantitykind> ;
  rdfs:label "Information Entropy"@en ;
  skos:broader quantitykind:Dimensionless .