"I Need to Find That One Chart": How Data Workers Navigate, Make Sense of, and Communicate Analytical Conversations
Ken Gu, Srishti Palani, Vidya Setlur

TL;DR
This paper explores how data workers navigate, interpret, and communicate complex analytical conversations in natural language interfaces, proposing structured tools to improve re-visitation and understanding.
Contribution
It introduces a design probe with structured elements to enhance navigation and summarization of analytical conversations, addressing limitations of linear transcript interfaces.
Findings
Participants used visual recall and sequential strategies for navigation.
Summarization included process details and contextual information.
Structured tools improved re-visitation of analytical conversations.
Abstract
Conversational interfaces are increasingly used for data analysis, enabling data workers to express complex analytical intents in natural language. Yet, these interactions unfold as long, linear transcripts that are misaligned with the iterative, nonlinear nature of real-world analyses. Revisiting and summarizing conversations for different contexts is therefore challenging. This paper investigates how data workers navigate, make sense of, and communicate prior analytical conversations. To study behaviors beyond those supported by standard interfaces (i.e., scrolling and keyword search), we develop a design probe that supplements analytical conversations with structured elements and affordances (e.g., filtering, multi-level navigation and detail-on-demand). In a user study (n = 10), participants used the probe to navigate and communicate past analyses, fulfilling information needs…
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Taxonomy
TopicsData Visualization and Analytics · Innovative Human-Technology Interaction · Personal Information Management and User Behavior
