lnu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Human Factors and Multilayer Networks
Vienna University of Technology, Austria.ORCID iD: 0000-0001-7880-8702
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). (ISOVIS;DISA-VAESS)ORCID iD: 0000-0002-0519-2537
2019 (English)In: Workshop on Visualization of Multilayer Networks (MNLVIS '19) at IEEE VIS '19, October 21, 2019, Vancouver, BC, Canada, 2019Conference paper, Published paper (Refereed)
Abstract [en]

Analysts of specific application domains, such as experts in systems biology or social scientists, are often interested to visually analyze a number of different network structures in conjunction, for example by using various visual structures of so-called multilayer networks. From the perspective of the human analyst, a sufficient perception and, consequently, a good understanding of those visual representations of multilayer networks is a non-trivial and often challenging task. Despite this practical importance and the clearly interesting visualization challenges, only few evaluation studies exist that investigate usability and cognitive issues of complex networks or, more specifically, multilayer networks. In this position paper, we address two main goals. On the one hand, we discuss existing studies from the fields of human-computer interaction and cognitive psychology that could inform the designers of multilayer network visualization in the future. On the other hand, we formulate first tentative recommendations for the design of multilayer networks, identify open issues in this context, and clarify possible future directions of research.

Place, publisher, year, edition, pages
2019.
Keywords [en]
Graph Drawing, Network Visualization, Visualization, Interaction, Cognition, Human Factors, Empirical Studies, Cognitive Load
National Category
Human Computer Interaction Computer Sciences
Research subject
Computer Science, Information and software visualization
Identifiers
URN: urn:nbn:se:lnu:diva-87106OAI: oai:DiVA.org:lnu-87106DiVA, id: diva2:1340974
Conference
Workshop on Visualization of Multilayer Networks (MNLVIS '19) at IEEE VIS '19, October 21, 2019, Vancouver, BC, Canada
Projects
DISA-VAESSAvailable from: 2019-08-07 Created: 2019-08-07 Last updated: 2022-02-22Bibliographically approved

Open Access in DiVA

fulltext(707 kB)179 downloads
File information
File name FULLTEXT01.pdfFile size 707 kBChecksum SHA-512
e234b76336a5b231eb1b7ffd629ed93cc75b8e09c322c7d0f4478b428857ed0fe6cbc4065cdaf928bc3cd6ae512fa9cf6c7e52d8583d820331ba3dc2b5f088c9
Type fulltextMimetype application/pdf

Other links

Workshop web page

Authority records

Kerren, Andreas

Search in DiVA

By author/editor
Pohl, MargitKerren, Andreas
By organisation
Department of computer science and media technology (CM)
Human Computer InteractionComputer Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 182 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 290 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf