• Canyon: Providing location awareness of multiple moving objects in a detail view on large displays

    A. Ion, B. Y. -L. Chang, M. Haller, M. Hancock, and S. D. Scott, “Canyon: Providing location awareness of multiple moving objects in a detail view on large displays,” in Proc. CHI, New York, NY, USA, 2013.

    @INPROCEEDINGS{ion:2013:canyon,
    author = {Alexandra Ion and Y.-L. Betty Chang and Michael Haller and Mark Hancock and Stacey D. Scott},
    title = {Canyon: Providing location awareness of multiple moving objects in a detail view on large displays},
    booktitle = {Proc. CHI},
    year = {2013},
    address = {New York, NY, USA},
    publisher = {ACM Press},
    note = {(Best Paper Honorable Mention Award)},
    abstract = {Overview+Detail interfaces can be used to examine the details of complex data while retaining the datas overall context. Dynamic data introduce challenges for these interfaces, however, as moving objects may exit the detail view, as well as a persons field of view if they are working at a large interactive surface. To address this "off-view" problem, we propose a new information visualization technique, called Canyon. This technique attaches a small view of an off-view object, including some surrounding context, to the external boundary of the detail view. The area between the detail view and the region containing the off-view object is virtually "folded" to conserve space. A comparison study was conducted contrasting the benefits and limitations of Canyon to an established technique, called Wedge. Canyon was more accurate across a number of tasks, especially more complex tasks, and was comparably efficient.},
    subtype = {conference}
    }


    Abstract

    Overview+Detail interfaces can be used to examine the details of complex data while retaining the datas overall context. Dynamic data introduce challenges for these interfaces, however, as moving objects may exit the detail view, as well as a persons field of view if they are working at a large interactive surface. To address this "off-view" problem, we propose a new information visualization technique, called Canyon. This technique attaches a small view of an off-view object, including some surrounding context, to the external boundary of the detail view. The area between the detail view and the region containing the off-view object is virtually "folded" to conserve space. A comparison study was conducted contrasting the benefits and limitations of Canyon to an established technique, called Wedge. Canyon was more accurate across a number of tasks, especially more complex tasks, and was comparably efficient.