Authors: Bowen Yu, Claudio Silva
Abstract: 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 system that utilizes the state-of-the-art natural language processing technique to assist dataflow diagram construction. FlowSense employs a semantic parser with special utterance tagging and utterance placeholders to generalize to different datasets and dataflow diagrams. It explicitly presents recognized dataset and diagram 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.