Repository logo
  • Communities & Collections
  • All of DSpace
  • English
  • ÄŒeÅ¡tina
  • Deutsch
  • Español
  • Français
  • Gàidhlig
  • LatvieÅ¡u
  • Magyar
  • Nederlands
  • Português
  • Português do Brasil
  • Suomi
  • Svenska
  • Türkçe
  • Қазақ
  • বাংলা
  • हिंदी
  • Ελληνικά
  • Log In
    or
    New user? Click here to register.Have you forgotten your password?
  1. Home
  2. Browse by Author

Browsing by Author "Tennekes, Martijn"

Now showing 1 - 2 of 2
Results Per Page
Sort Options
  • Loading...
    Thumbnail Image
    Item
    cols4all: a Color Palette Analysis Tool
    (The Eurographics Association, 2023) Tennekes, Martijn; Puts, Marco J. H.; Hoellt, Thomas; Aigner, Wolfgang; Wang, Bei
    cols4all is a software tool to analyse and compare color palettes, using several properties, including color blind friendliness and fairness, which checks whether all palette colors stand out about equally.
  • Loading...
    Thumbnail Image
    Item
    Design Space of Origin-Destination Data Visualization
    (The Eurographics Association and John Wiley & Sons Ltd., 2021) Tennekes, Martijn; Chen, Min; Borgo, Rita and Marai, G. Elisabeta and Landesberger, Tatiana von
    Visualization is an essential tool for observing and analyzing origin-destination (OD) data, which encodes flows between geographic locations, e.g., in applications concerning commuting, migration, and transport of goods. However, depicting OD data often encounter issues of cluttering and occlusion. To address these issues, many visual designs feature data abstraction and visual abstraction, such as node aggregation and edge bundling, resulting in information loss. The recent theoretical and empirical developments in visualization have substantiated the merits of such abstraction, while confirming that viewers' knowledge can alleviate the negative impact due to information loss. It is thus desirable to map out different ways of losing and adding information in origin-destination data visualization (ODDV).We therefore formulate a new design space of ODDV based on the categorization of informative operations on OD data in data abstraction and visual abstraction. We apply this design space to existing ODDV methods, outline strategies for exploring the design space, and suggest ideas for further exploration.

Eurographics Association © 2013-2025  |  System hosted at Graz University of Technology      
DSpace software copyright © 2002-2025 LYRASIS

  • Cookie settings
  • Privacy policy
  • End User Agreement
  • Send Feedback