Challenges in Multilayer Network Visualization and Analysis Workshop

 

Multiple types of nodes/edges in a network are often flattened into a single network. However, real-world data and systems are often more accurately modelled as a set of interacting networks, or layers, with different node and edge types. These so-called Multilayer Networks are studied by researchers both in network visualization and in complex systems. Multilayer Networks provide new challenges for visualization, visual analytics, interaction, and modelling. New tasks and domain problems arise,  which are not yet addressed by existing visual analytics approaches.

This workshop will focus on the contributions possible from the information visualization and visual analytics communities to advance visual analytics of Multilayer Networks. The workshop provides a platform for short presentations on urgent challenges, innovative ideas, new frameworks, novel design concepts, fundamental requirements, and work in progress related to the workshop topic.

The workshop keynote will be given by Guy Melançon, University of Bordeaux (FR): Prof. Melançon’s primary research area is network visual analytics, focusing specifically on multilayer and dynamic networks, with extensive experience in multi-disciplinary research projects. The application domains of his work have included human trafficking networks, digital ethnography, historical archives, spatial geography, and software engineering. He was an organizer of the recent Dagstuhl Seminar on “Visual Analytics of Multilayer Networks across Disciplines” (#19061).

Objectives

This workshop is a venue for discussion of the emerging topic of Multilayer Networks . The vision is to stimulate research on Multilayer Networks within the wider visualization and visual analytics communities. Building from a successful Dagstuhl seminar on "Visualization of Multilayer Networks Across Disciplines" (#19061), we would like to bring the complex network and application domain perspective to this platform through talks and short presentations.

Specifically, the primary goals of this workshop are:

1. To clearly identify and present the specific challenges of Multilayer Networks to the visual analytics and visualization communities.

2. To provide support for a community of visualization researchers to foster creation and evaluation of innovative visual analytics solutions that can be applied to the topic of Multilayer Networks.

3. To provide a significant platform in visualization for ideas sourced from the wide range of domains contributing to Multilayer Networks. Bringing in such a diverse set of research ideas will allow us to identify interdisciplinary challenges and foster future interdisciplinary collaborations.

Topics

The workshop will focus on  the following subtopics specifically (however other topics may be included):

  • A unifying visualization framework for Multilayer Networks: Multilayer Networks have been known in visualization under various names and concepts. Therefore, there is a need for a unified visualization framework for Multilayer Network visualization, interaction and analytics, that focuses on the visualization challenges raised by the underlying mathematical framework.
  • Novel visual encodings: Multilayer Networks raise the need to develop new visualization techniques that allow for the display of the complexity of the networks and their structure.
  • Interdisciplinarity: The diverse range of application domains results in a vast range of complex data sets and novel problems that may be best addressed by new visualization approaches. The existing body of Multilayer Network research in the fields of Complex Systems and Social Network Analysis also provides additional tools and analytical approaches to these problems.
  • Multiple layers and attributes: The complex systems which are modelled as Multilayer Networks often are multivariate in nature. Encoding and visualization of these attributes within the multilayer structure, possibly as nodes of another layer, raises many possibilities.
  • Network Science: Additionally understanding the analytical relationship between layers (with respect to structure and/or attributes) and supporting layer comparison raises many interesting challenges and opportunities for visualization. Finally, network science provides many new metrics for the multilayer use case, which offer new possibilities for visual analytics.
  • Interaction: Dealing with layers as objects in a visual analytics system results in new tasks, and possibly interaction techniques.
  • Evaluation & Human Factors: The complexity of the network structure and its visual encoding raises the challenges of assessing the perceptual and cognitive aspects when interactively visualizing the networks. Many of the systems, which are developed within the context of application domains, lack a thorough empirical evaluation. The existing methodologies and rigour found in the information visualization and HCI communities, need to be adapted for the Multilayer Networks use case.

Programme

https://www.multilayernetvis.org/programme/programme/

Partners

     

 

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Practical Infos

The official workshop website, including the workshop programme and accepted submissions, can be found at

https://www.multilayernetvis.org/

Contact

Dr Fintan MC GEE
Dr Fintan MC GEE
Send an e-mail
Dr Mohammad GHONIEM
Dr Mohammad GHONIEM
Send an e-mail

Further information

The organisers wish to thank Schloss Dagstuhl for hosting Seminar #19061 on “Visual Analytics of Multilayer Networks across Disciplines”, of which this workshop is an outcome. This workshop is was also partially funded by the BLIZAAR project on Multilayer Network Visualization (an international co operation co-funded by the French ANR grant BLIZAAR ANR-15-CE23-0002-01 and the Luxembourgish FNR grant BLIZAAR INTER/ANR/14/9909176) and the HiGHmed Project funded within German BMBF Medical Informatics initiative.