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Facilitating Exploration with Interaction Snapshots under High Latency

机译:在高延迟下促进互动快照的探索

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Latency is, unfortunately, a reality when working with large data sets. Guaranteeing imperceptible latency for interactivity is often prohibitively expensive: the application developer may be forced to migrate data processing engines or deal with complex error bounds on samples, and to limit the application to users with high network bandwidth. Instead of relying on the backend, we propose a simple UX design—interaction snapshots. Responses of requests from the interactions are asynchronously loaded in "snapshots". With interaction snapshots, users can interact concurrently while the snapshots load. Our user study participants found it useful not to have to wait for each result and easily navigate to prior snapshots. For latency up to 5 seconds, participants were able to complete extrema, threshold, and trend identification tasks with little negative impact.
机译:遗憾的是,使用大数据集时的现实是现实。保证相互作用的难以察觉的延迟通常是昂贵的:应用程序开发人员可以被迫迁移数据处理引擎或处理样本上的复杂错误界限,并将应用程序限制为具有高网络带宽的用户。我们不依赖后端,我们提出了一个简单的UX设计 - 交互快照。来自交互的请求的响应是异步加载的“快照”。使用交互快照,用户可以在快照加载时同时交互。我们的用户学习参与者发现它很有用不需要等待每个结果,并且轻松导航到先前的快照。对于高达5秒的延迟,参与者能够完成极值,门槛和趋势识别任务,具有很少的负面影响。

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