Call for help: Multilayers/Multimodals and Uncertainty in humanities network visualisation

Dear all,
Today I would like to ask you for your help with two papers on network analysis visualization in the Humanities. One I co-author, the second one is co-authored by a colleague.
For both we are equally interested in solutions which were created with standard software (Gephi, Netdraw, Nodegoat etc.) and custom-made visualisations. If in doubt, please email what you consider interesting in this context to info@historicalnetworkresearch.org.

 

Multilayer/Multimodal networks

The first paper deals with network data which represents complexity beyond unipartite/bipartite network models. We are looking for examples of humanities network visualisations which for example take the form of

  • Networks with multiple interlinked layers
  • Networks with multiple types of edges and nodes
  • Networks of networks
  • Interactive systems for the exploration of network datasets

This paper seeks to identify challenges for network visualisations in the Humanities and any pointers to work which exceeds the usual boundaries in complexity is most welcome.

 

Uncertainty

The second paper (which I co-author) deals with the problem of representing uncertainty in humanities network data. I would be grateful if you could comment and point us to any work you know which addresses this problem visually or as part of data modeling.

  • How should uncertainty (not) be represented?
  • When do we (not) need to make uncertainty explicit?
  • Did or do you encounter problems concerning uncertainty in your own projects? If yes, could you provide a reference or/and could you briefly report what kind of uncertainty occurred and what kind of data was used?

The purpose of the paper is to establish a status quo of existing practices within Digital Humanities and other domains with expertise in data visualisation, to identify challenges and to point to possible solutions.

Thank you and greetings,
Marten

Published by Marten Düring
January 30, 2019

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