WG3: Visual analytics of knowledge spaces – knowledge maps

WG3

Main scientific objective:
Visualization principles for knowledge maps (O2,3)

Specific objectives, means and methods:

  • Analyse and visualize complex universal knowledge classification systems of specific knowledge domains (e.g. bibliographic classifications such as the Universal Decimal Classification and subject category systems in databases) and large scale knowledge spaces
  • Map the principal dimensions of information spaces as well as their occupation by a collection of objects
  • Explore clustering-based visualizations
  • Integrate different science and knowledge maps
  • Outline the best practices of knowledge mapping
  • Create a typology of knowledge maps

 

Members (33)

Working group leader: Almila AKDAG SAHAL, Renaud LAMBIOTTE

Andreas RAUBER, Nikolay VITANOV, Lorna WILDGAARD, Santo FORTUNATO, Sebastien HEYMANN, Marton KARSAI, Bin YANG, David CHAVALARIAS, Clement LEVALLOIS, Panayiota POLYDORATOU, Janos KERTESZ, Sorin SOLOMON, Judit BAR-ILAN, Giulia ROTUNDO, Ciro CATTUTO, Silvana STEFANI, Orion PENNER, Vincent TRAAG, Loet LEYDESDORFF, Marc BRON, Veslava OSINSKA, Maxi SAN MIGUEL,  Ismael RAFOLS, Emilia GOMEZ-GUTIERREZ, Esteban Romero FRIAS, Martin ROSVALL, Senka ANASTASOVA, Vladimir LEKOVSKI, Mark HALL, Zsuzsanna VARGA, Andrea SCHARNHORST

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