Kandinsky: Visual Analytics of the Avant‐Garde

Abstract The Avant‐Garde of the early 20th‐century was characterized by thriving artistic collaborations that gave rise to overlapping movements such as Expressionism, Cubism and Futurism. Although exhibitions acted as central hubs, the resulting artists' networks remain difficult to investigate due to inconsistent documentation, uneven temporal coverage, and rapidly shifting geographic contexts. We introduce Kandinsky , a Visual Analytics approach tailored to uncovering Avant‐Garde exhibition networks. Kandinsky combines a radial clustering layout that captures cohesive artistic ensembles with coordinated views, situating exhibition activity across time and region to enable a structured analysis of historically situated artistic relations. A task‐based validation and usability study with ten experts, supported by an extended case study, show that Kandinsky traces structural communities, transnational and temporal relations, and previously unrecognized patterns. This offers a data‐driven complement to traditional art‐historical inquiry.

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Publication Details

Journal
Computer Graphics Forum
Published
2026-10-27
DOI
https://doi.org/10.1111/cgf.70654
Primary Topic
Data Visualization and Analytics
Type
article
Field-Weighted Citation Impact
0.00

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Kandinsky: Visual Analytics of the Avant‐Garde

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Computer Graphics Forum
Data Visualization and Analytics
article

Kandinsky: Visual Analytics of the Avant‐Garde

Velitchko Filipov, Raphaël Rosenberg, Silvia Miksch, Raphael Buchmüller, Sara Di Bartolomeo, Michaela Tuscher, Teresa Kamencek, Daniel Keim, Luisa Müller
article en

Abstract

Abstract The Avant‐Garde of the early 20th‐century was characterized by thriving artistic collaborations that gave rise to overlapping movements such as Expressionism, Cubism and Futurism. Although exhibitions acted as central hubs, the resulting artists' networks remain difficult to investigate due to inconsistent documentation, uneven temporal coverage, and rapidly shifting geographic contexts. We introduce Kandinsky , a Visual Analytics approach tailored to uncovering Avant‐Garde exhibition networks. Kandinsky combines a radial clustering layout that captures cohesive artistic ensembles with coordinated views, situating exhibition activity across time and region to enable a structured analysis of historically situated artistic relations. A task‐based validation and usability study with ten experts, supported by an extended case study, show that Kandinsky traces structural communities, transnational and temporal relations, and previously unrecognized patterns. This offers a data‐driven complement to traditional art‐historical inquiry.

Computer Graphics Forum
University of Vienna (AT), TU Wien (AT), University of Konstanz (DE)
Technische Universitat Wien, Austrian Science Fund, Technische Universität Wien
Openalex Percentile: Top 30%
Data Visualization and Analytics
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