Abstract
How information is distributed between internal and external representations significantly affects information search performance. For a distributed information search task, data representation and cognitive distribution jointly affect the user search performance in terms of response time and accuracy. Guided by UFuRT ( User, Function, Representation, Task), a human-centered framework, we propose a search model and task taxonomy. The model defines its application in the context of healthcare setting. The taxonomy clarifies the legitimate operations for each type of search task of relation data. We then developed experimental prototypes of hyperlipidemia data displays. Based on the displays, we tested the search tasks performance through two experiments. The experiments are of a within-subject design with a sample of 24 participants. The results in general support our hypothesesand validate the prediction of the model and task taxonomy.
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