Interactive Exploration of Large-Scale UI Datasets with Design Maps

Luis A. Leiva*, Asutosh Hota, Antti Oulasvirta

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)

Abstract

Designers are increasingly using online resources for inspiration. How to best support design exploration without compromising creativity? We introduce and study Design Maps, a class of point-cloud visualizations that makes large user interface datasets explorable. Design Maps are computed using dimensionality reduction and clustering techniques, which we analyze thoroughly in this paper. We present concepts for integrating Design Maps into design tools, including interactive visualization, local neighborhood exploration and functionality to integrate existing solutions to the design at hand. These concepts were implemented in a wireframing tool for mobile apps, which was evaluated with actual designers performing realistic tasks. Overall, designers find Design Maps supporting their creativity (avg. CSI score of 74/100) and indicate that the maps producing consistent whitespacing within cloud points are the most informative ones.

Original languageEnglish
Pages (from-to)490-509
Number of pages20
JournalInteracting with Computers
Volume32
Issue number5
DOIs
Publication statusPublished - 1 Sep 2020
MoE publication typeA1 Journal article-refereed

Keywords

  • design tools
  • interaction design
  • unsupervised learning
  • visualization

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