<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:rights>CC BY 2.0 AT</dc:rights>
  <dc:rights>http://creativecommons.org/licenses/by/2.0/at/</dc:rights>
  <dc:title xml:lang="eng">Screenshot from the study prototype explaining one of the four visualization techniques - Horizon Graphs (HG)</dc:title>
  <dc:subject xml:lang="eng">visualization, user study, evaluation, time series, spatial data, collapsed horizon graphs, compact boxplots, braided graphs</dc:subject>
  <dc:date>2019</dc:date>
  <dc:type xml:lang="eng">Image</dc:type>
  <dc:description xml:lang="eng">In this user study we compare four different visualization techniques of times series in a spatial context using small multiples. 
Horizon Graphs divide the line graph of a time series into non-overlapping bands and apply a sequential/diverging color mapping to the time series. These bands are then layered in a top-to-bottom fashion to reduce the required height. In order to fit the spatial dimensions the Horizon Graph is shrunk horizontally. This screenshot explains the construction steps of Horizon Graphs.</dc:description>
  <dc:identifier>https://phaidra.ustp.at/o:3577</dc:identifier>
  <dc:creator>Dahnert, Manuel</dc:creator>
  <dc:creator>Kehrer, Johannes</dc:creator>
  <dc:creator>Aigner, Wolfgang</dc:creator>
  <dc:creator>Rind, Alexander</dc:creator>
  <dc:language>eng</dc:language>
  <dc:format>image/jpeg</dc:format>
</oai_dc:dc>