Unifying the framework of Multi-Layer Network and Visual Analytics

Søren Knudsen (1, 2) , Jan Aerts (3) , Daniel Archambault (4) , Remco Chang (5) , Jean-Daniel Fekete (6) , Martin Grandjean (7) , Jessie Kennedy (8) , Mikko Kivelä (9) , Matteo Magnani (10) , Helen Purchase (11) , Christian Tominski (12) , Paola R Valdivia (6) , Tatiana von Landesberger (13)

1 University of Calgary
2 UCPH - University of Copenhagen = Københavns Universitet
3 UHasselt - Hasselt University
4 Department of Computer Science [Swansea]
5 Tufts University [Medford]
6 AVIZ - Analysis and Visualization
7 UNIL - Université de Lausanne = University of Lausanne
8 Edinburgh Napier University
9 Aalto University School of Science and Technology [Aalto, Finland]
10 Uppsala University
11 Department of Computing Science
12 Computer Science and Electrical Engineering
13 Department of Computer Science

The notion of multi-layer networks introduces a general framework and common vocabulary for existing ideas in complex network theory. In doing so, it is possible to understand and compare these dierent ideas in a new and more fruitful manner. However, to make this operationalizable to the visualization and visual analytics community, we need more clarity. For example: What is a layer? What are the semantics of interlayer edges, and specifically, identity links between layers? Can dierent multilayered networks be expressed or implemented in the same way? And vice versa, can one multilayered network be expressed or implemented in dierent ways?

Keywords: Networks; Social network analyses; Complexity; Complex networks; Multi-layer networks; Data visualisation; Data visualization; Information design; graph theory

Domains: Computational Complexity [cs.CC]; Methods and statistics; Library and information sciences; Social and Information Networks [cs.SI]

Søren Knudsen, Jan Aerts, Daniel Archambault, Remco Chang, Jean-Daniel Fekete, et al.. Unifying the framework of Multi-Layer Network and Visual Analytics. Visual Analytics of Multilayer Networks Across Disciplines, 9 (2), pp.19-23, 2019, Dagstuhl Reports. ⟨hal-02185272⟩