Section: Partnerships and Cooperations

European Initiatives

Collaborations in European Programs, Except FP7 & H2020

  • Program: ANR PRCI

  • Project acronym: MicroVis

  • Project title: Micro visualizations for pervasive and mobile data exploration

  • Duration: 11/2019 - 08/2022

  • Coordinator: Petra Isenberg

  • Other partners: University of Stuttgart

  • Abstract: The goal of this joint Franco-German project is to study very small data visualizations, micro visualizations, in display contexts that can only dedicate minimal rendering space for data representations. We will study human perception of and interaction with micro visualizations given small as well as complex data. The increasing demand for data visualizations on small mobile devices such as fitness tracking armbands, smart watches, or mobile phones drives our research. Given this usage context, we focus on situations in which visualizations are used “on the go,” while walking, riding a vehicle, or running. It is still unclear to which extent our knowledge of desktop-sized visualizations transfers to contexts that involve minimal display space, diverse viewing angles, and moving displays.

  • Program: 2016 FWF–ANR Call for French-Austrian Joint Projects

  • Project acronym: ILLUSTRARE

  • Project title: Integrative Visual Abstraction of Molecular Data

  • Duration: 48 months

  • Coordinator: Tobias Isenberg and Ivan Viola

  • Other partners: TU Wien, Austria

  • Abstract: The essential building block of visualization is the phenomenon of visual abstraction. While visual abstraction is intuitively understood, there is no scientific theory associated with it that would be useful in the visualization synthesis process. Our central aim of this project is thus to gain better understanding of the visual abstraction characteristics. We lay down a hypothetical initial basis of theoretical foundations of visual abstractions in the proposal. We hypothesize that visual abstraction is a multidimensional phenomenon that can be spanned by axes of abstraction. Besides abstractions associated with a static structure we take a closer look at abstractions related to dynamics, procedures, and emergence of the structure. We also study abstraction characteristics related to multi-scale phenomena defined both in space and in time. This hypothetical basis is either supported or rejected by means of exemplary evidence from the specific application domain of structural biology. Structural biology data is very complex, it includes the aspect of emergence and it is defined over multiple scales. Furthermore, abstraction has led to key discoveries in biology, such as the organization of the DNA. We study the multiscale visual abstraction characteristics on the visualization of long nucleic strands and the abstractions that convey emerging phenomena on visualization of molecular machinery use cases. From these two fields we work toward a theory of visual abstraction in a bottom-up manner, investigating the validity of the theory in other application domains as well.

  • Program: CHIST-ERA

  • Project acronym: IVAN

  • Project title: Interactive and Visual Analysis of Networks

  • Duration: May 2018 - April 2021

  • Coordinator: Dr. Torsten Möller, Uni Wien, Austria

  • Other partners: EPFL, Switzerland, Inria France, Uni Wien, Austria

  • Abstract: The main goal of IVAN is to create a visual analysis system for the exploration of dynamic or time-dependent networks (from small to large scale). Our contributions will be in three principal areas:

    1. novel algorithms for network clustering that are based on graph harmonic analysis and level-of-detail methods;

    2. the development of novel similarity measures for networks and network clusters for the purpose of comparing multiple network clusterings and the grouping (clustering) of different network clusterings; and

    3. a system for user-driven analysis of network clusterings supported by novel visual encodings and interaction techniques suitable for exploring dynamic networks and their clusterings in the presence of uncertainties due to noise and uncontrolled variations of network properties.

    Our aim is to make these novel algorithms accessible to a broad range of users and researchers to enable reliable and informed decisions based on the network analysis.

Collaborations with Major European Organizations

  • The Bauhaus-Universität Weimar (Germany)

  • Steve Haroz collaborates with Florian Echtler to analyze research transparency in human-computer interaction.

  • Hasso Plattner Institute (Germany)

  • Pierre Dragicevic and Tobias Isenberg collaborate with Amir Semmo on stylization filters for facilitating the examination of disturbing visual content.

  • University of Zurich (Switzerland)

  • Pierre Dragicevic and Steve Haroz collaborate with Chat Wacharamanotham on transparent statistical reporting and efficient statistical communication.

  • KU Leuven (Belgium)

  • Pierre Dragicevic collaborates with Andrew Vande Moere on a survey on data physicalization.

  • Linköping University (Sweden)

  • Tobias Isenberg, Xiyao Wang, and Mickael Sereno collaborate with Lonni Besançon on interaction with 3D visualization.

  • University of Granada (Spain)

  • Tobias Isenberg collaborates with Domingo Martin and German Arroyo on digital stippling.

  • University of Roma (Italy), TU Darmstadt (Germany)

  • Jean-Daniel Fekete Fekete collaborates with Giuseppe Santucci, Carsten Binnig and colleagues on the design of database benchmarks to better support visualization;

  • University of Bari (Italy)

  • Jean-Daniel Fekete collaborates with Paolo Buono on hypergraph visualization;

  • University of Konstanz (Germany)

  • Petra Isenberg collaborated with Johannes Fuchs and Anastasia Bezerianos on visualization for teaching clustering algorithms.