IEEE Trans Vis Comput Graph. 2020 Jan;26(1):1-11. doi: 10.1109/TVCG.2019.2934668. Epub 2019 Aug 20.
Dataflow visualization systems enable flexible visual data exploration by allowing the user to construct a dataflow diagram that composes query and visualization modules to specify system functionality. However learning dataflow diagram usage presents overhead that often discourages the user. In this work we design FlowSense, a natural language interface for dataflow visualization systems that utilizes state-of-the-art natural language processing techniques to assist dataflow diagram construction. FlowSense employs a semantic parser with special utterance tagging and special utterance placeholders to generalize to different datasets and dataflow diagrams. It explicitly presents recognized dataset and diagram special utterances to the user for dataflow context awareness. With FlowSense the user can expand and adjust dataflow diagrams more conveniently via plain English. We apply FlowSense to the VisFlow subset-flow visualization system to enhance its usability. We evaluate FlowSense by one case study with domain experts on a real-world data analysis problem and a formal user study.
数据流可视化系统通过允许用户构建一个数据流图来组合查询和可视化模块以指定系统功能，从而实现灵活的数据可视化探索。然而，学习数据流图的使用会带来开销，这通常会使用户望而却步。在这项工作中，我们设计了 FlowSense，这是一种用于数据流可视化系统的自然语言接口，它利用最先进的自然语言处理技术来协助数据流图的构建。FlowSense 采用了带有特殊语句标记和特殊语句占位符的语义解析器，以推广到不同的数据集和数据流图。它将识别出的数据集和图特殊语句明确呈现给用户，以实现数据流上下文感知。通过 FlowSense，用户可以更方便地使用英语扩展和调整数据流图。我们将 FlowSense 应用于 VisFlow 子集流可视化系统，以增强其可用性。我们通过对领域专家在真实数据分析问题上的案例研究和正式用户研究来评估 FlowSense。
