Hue tinting’ is a set of visualization interactions that make it possible to use color in ways that are meaningful and specific to visualization tasks. ‘Hue tinting’ interactions address the problem of how to best choose colors to show numbers while 1) using hue to mark only relevant aspects of the data and 2) minimizing color-related problems such as brightness distortion. Most visualization systems make it difficult to use hue variation to identify and distinguish between meaningful features in a dataset without distorting the form or structure of the data. Like colorizing a black-and-white photograph, ‘Hue tinting’ lets you use color to select, identify, and mark relevant portions of your data without distorting the brightness of the underlying grayscale visualization. Hue tinting a specific range of data values provides a direct method for validating and compliance-testing. Hue tinting a specific region of an image provides a direct method for identifying and measuring features in a dataset, such as the range of power levels at a given frequency range.
The web is enormous and constantly growing. User-interfaces for web-based applications need to make it easy for people to access relevant information without becoming overwhelmed or disoriented. Today's interfaces employ textual representations almost exclusively, typically organized in lists and hierarchies of web-page titles or URL taxonomies. Given the ability of images to assist memory and our frequent exploitation of space in everyday problem solving to simplify choice, perception, and mental computation, it is surprising that so little use is made of images and spatial organizations in accessing and organizing web information. The work we summarize in this paper suggest that spatial and temporal organization of selectable images may offer multiple advantages over textual lists of titles and URLs. We describe several image-based applications, detail basic image representation techniques, and discuss spatial and temporal strategies for organization.
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