Abstract data: Difference between revisions

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{{Definition|'''Abstract data''' refers to ''(heterogenous)'' data that has no inherent spatial structure; thus it does not allow for a straightforward mapping to any geometry, but relies upon means provided by [[information visualization]] for its visual representation.}}
{{Definition|'''Abstract data''' refers to ''(heterogenous)'' data that has no inherent spatial structure; thus it does not allow for a straightforward mapping to any geometry, but relies upon means provided by [[information visualization]] for its visual representation.}}


Therefore creating a ''[[virtual reality]] (VR)'' is essential to visualizing abstract data. To allow intuitive understanding and to find wide acceptance, virtual spaces will be based on a ''real–world analogue'' that mostly supports human cognitive abilities.  
{{Quotation|Information visualization is visualization of abstract data. This is data that has no inherent mapping to space. Examples for abstract data are the results of a survey or a database of the staff of a company containing names, addresses, salary and other attributes.|[Voigt, 2002]}}
 


== References ==
== References ==


*[http://fabdp.fh-potsdam.de/daessler/paper/uom0595/tut.html]Rolf Daessler, ''Visualization of Abstract Information'', 1995.
*[Daessler, 1995]: Rolf Daessler, [http://fabdp.fh-potsdam.de/daessler/paper/uom0595/tut.html Visualization of Abstract Information], Created at: 1995, Retrieved at: 2004. http://fabdp.fh-potsdam.de/daessler/paper/uom0595/tut.html
*[http://www.vrvis.at/vis/resources/DA-RVoigt/node4.html]Robert Voigt, ''Classification and Definition of Terms'', 2002.
*[Voigt, 2002]: Robert Voigt, [http://www.vrvis.at/via/resources/DA-RVoigt/masterthesis.html An Extended Scatterplot Matrix and Case Studies in Information Visualization], Master's thesis, Hochschule Magdeburg-Stendal, 2002, [http://www.vrvis.at/vis/resources/DA-RVoigt/node4.html ''Classification and Definition of Terms'']
 
<timeline>
ImageSize  = width:160 height:550
PlotArea  = width:50 height:530 left:50 bottom:10
 
DateFormat = yyyy
Period    = from:1919 till:1991
TimeAxis  = orientation:vertical
ScaleMajor = unit:year increment:5 start:1920
 
# there is no automatic collision detection,
# so shift texts up or down manually to avoid overlap
 
Define $dx = 25 # shift text to right side of bar
 
PlotData=
  bar:Leaders color:red width:25 mark:(line,white) align:left fontsize:S


  from:start till:1922 shift:($dx,15)  text:Vladimir~Ilyich~[[Lenin]]
  from:1922  till:1953 shift:($dx,5)    text:[[Stalin|Josef Stalin]]
  from:1953  till:1964 shift:($dx,5)    text:Nikita~[[Khrushchev]]
  from:1964  till:1982 shift:($dx,5)    text:Leonid~[[Brezhnev]]
  from:1982  till:1984 shift:($dx,-12)  text:Yuri~[[Andropov]]
  from:1984  till:1985 shift:($dx,4)    text:Konstantin~[[Chernenko]] fontsize:XS
  from:1985  till:end  shift:($dx,10)  text:Mikhail~[[Gorbachev]]
</timeline>


[[Category: Glossary]]
[[Category: Glossary]]

Latest revision as of 10:58, 21 September 2006

Abstract data refers to (heterogenous) data that has no inherent spatial structure; thus it does not allow for a straightforward mapping to any geometry, but relies upon means provided by information visualization for its visual representation.
Information visualization is visualization of abstract data. This is data that has no inherent mapping to space. Examples for abstract data are the results of a survey or a database of the staff of a company containing names, addresses, salary and other attributes.
[Voigt, 2002]



References[edit]

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