Effective data analysis ideally requires the analyst to have high expertise as well as high knowledge of the data. Even with such familiarity, manually pursuing all potential hypotheses and exploring all possible views is impractical. We present DataSite, a proactive visual analytics system where the burden of selecting and executing appropriate computations is shared by an automatic server-side computation engine. Salient features identified by these automatic background processes are surfaced as notifications in a feed timeline. DataSite effectively turns data analysis into a conversation between analyst and computer, thereby reducing the cognitive load and domain knowledge requirements. We validate the system with a user study comparing it to a recent visualization recommendation system, yielding significant improvement, particularly for complex analyses that existing analytics systems do not support well.

中文翻译：

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DataSite：主动式可视化数据探索，计算基于洞察力的建议

理想情况下，有效的数据分析要求分析师具有高度的专业知识和对数据的高度了解。即使如此熟悉，手动追求所有可能的假设并探索所有可能的观点也是不切实际的。我们展示了 DataSite，这是一个主动的可视化分析系统，其中选择和执行适当计算的负担由自动服务器端计算引擎分担。由这些自动后台进程识别的显着特征在提要时间线中显示为通知。DataSite 有效地将数据分析转变为分析师与计算机之间的对话，从而降低认知负荷和领域知识需求。我们通过用户研究来验证该系统，将其与最近的可视化推荐系统进行比较，产生了显着的改进，