By Ed H. Chi (auth.)

ISBN-10: 904816009X

ISBN-13: 9789048160099

ISBN-10: 9401705739

ISBN-13: 9789401705738

Fundamental suggestions in knowing info were elusive for a very long time. the sector of man-made Intelligence has proposed the Turing try out with the intention to try out for the "smart" behaviors of desktop courses that convey human-like characteristics. corresponding to the Turing try for the sector of Human­ details interplay (HII), getting details to the folk that desire them and assisting them to appreciate the knowledge is the hot problem of the net period. In a brief period of time, the infrastructure of the internet turned ubiquitious not only when it comes to protocols and transcontinental cables but additionally by way of daily units able to recalling network-stored facts, occasionally cord­ lessly. for this reason, as those infrastructures turn into fact, our realization on HII matters must shift from details entry to details sensemaking, a comparatively new time period coined to explain the method of digesting info and knowing its constitution and intricacies that allows you to make judgements and take action.

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The gulf of execution is evidence that the operation and interaction model of a visualization system often hampers the analysis process because it does not fulfill the needs ofthe analysis. We can construct similar seenarios by examining other data domains, such as visualizing hierarchical structures like file systems or organizational charts, slices of a 3D human brain, or world-wide web linkage structures. Fundamentally, each of these data domains have data and its associated visualized view, therefore filtering actions in these data domains will also have the same exact ambiguous meanings.

Builders of general visualization systems are thus encouraged to have modular and extensible systems for specific application domains. For example, in our experience, we have applied this framework to our Visualization Spreadsheet system and extended it to multiple data domains, which we present in Chapter 5. 2 End-User Advantages using this Framework Of these three types of users, the end-user matters most, because the visualization model must help the end-users achieve their goals faster and easier.

For instance, for an image, since the value is the image pixel values, the modification of the colormap represents a raw pixel value modification, and therefore, should be classified as a value operator. However, in a 3D surface heat map, the modification of the heat color scale appears to be a view change that does not fundamentally change the underlying surface values. Another example is the HorneFinder [2] application in Section 1. Sometimes we would like to apply filtering to generate a data set.

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A Framework for Visualizing Information by Ed H. Chi (auth.)


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