Abstract

TopoText is a context-preserving technique for visualizing text data for multi-scale spatial aggregates to gain insight into spatial phenomena. Conventional exploration requires users to navigate across multiple scales but only presents the information related to the current scale. This limitation potentially adds more steps of interaction and cognitive overload to the users. TopoText renders multi-scale aggregates into a single visual display combining novel text-based encoding and layout methods that draw labels along the boundary or filled within the aggregates. The text itself not only summarizes the semantics at each individual scale, but also indicates the spatial coverage of the aggregates and their underlying hierarchical relationships. We validate TopoText with both a user study as well as several application examples.

Original languageEnglish (US)
Title of host publicationCHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems
Subtitle of host publicationEngage with CHI
PublisherAssociation for Computing Machinery
Volume2018-April
ISBN (Electronic)9781450356206, 9781450356213
DOIs
StatePublished - Apr 20 2018
Event2018 CHI Conference on Human Factors in Computing Systems, CHI 2018 - Montreal, Canada
Duration: Apr 21 2018Apr 26 2018

Other

Other2018 CHI Conference on Human Factors in Computing Systems, CHI 2018
CountryCanada
CityMontreal
Period4/21/184/26/18

Fingerprint

Labels
Semantics
Display devices

Keywords

  • Context preservation
  • Geospatial visualization
  • Multi-scale analysi
  • Text visualization
  • Typographic map

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design
  • Software

Cite this

Zhang, J., Surakitbanharn, C., Elmqvist, N., Maciejewski, R., Qian, Z., & Ebert, D. S. (2018). TopoText: Context-preserving Text data exploration across multiple spatial scales. In CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems: Engage with CHI (Vol. 2018-April). Association for Computing Machinery. https://doi.org/10.1145/3173574.3173611

TopoText : Context-preserving Text data exploration across multiple spatial scales. / Zhang, Jiawei; Surakitbanharn, Chittayong; Elmqvist, Niklas; Maciejewski, Ross; Qian, Zhenyu; Ebert, David S.

CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems: Engage with CHI. Vol. 2018-April Association for Computing Machinery, 2018.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Zhang, J, Surakitbanharn, C, Elmqvist, N, Maciejewski, R, Qian, Z & Ebert, DS 2018, TopoText: Context-preserving Text data exploration across multiple spatial scales. in CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems: Engage with CHI. vol. 2018-April, Association for Computing Machinery, 2018 CHI Conference on Human Factors in Computing Systems, CHI 2018, Montreal, Canada, 4/21/18. https://doi.org/10.1145/3173574.3173611
Zhang J, Surakitbanharn C, Elmqvist N, Maciejewski R, Qian Z, Ebert DS. TopoText: Context-preserving Text data exploration across multiple spatial scales. In CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems: Engage with CHI. Vol. 2018-April. Association for Computing Machinery. 2018 https://doi.org/10.1145/3173574.3173611
Zhang, Jiawei ; Surakitbanharn, Chittayong ; Elmqvist, Niklas ; Maciejewski, Ross ; Qian, Zhenyu ; Ebert, David S. / TopoText : Context-preserving Text data exploration across multiple spatial scales. CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems: Engage with CHI. Vol. 2018-April Association for Computing Machinery, 2018.
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