2022/10/07 by Rock Yuren Pang, Pang, Rock Yuren, Ruotong Wang +5 · 1 citation
Business, Management and Accounting · Computer Science · Decision Sciences · #Big Data and Business Intelligence #Data Visualization and Analytics #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Scientific Computing and Data Management
paper · pdf · doi:10.48550/arxiv.2210.03305
openalex publication_date 2022/10/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Data science workers increasingly collaborate on large-scale projects before communicating insights to a broader audience in the form of visualization. While prior work has modeled how data science teams, oftentimes with distinct roles and work processes, communicate knowledge to outside stakeholders, we have little knowledge of how data science workers communicate intermediately before delivering the final products. In this work, we contribute a nuanced description of the intermediate communication process within data science teams. By analyzing interview data with 8 self-identified data science workers, we characterized the data science intermediate communication process with four factors, including the types of audience, communication goals, shared artifacts, and mode of communication. We also identified overarching challenges in the current communication process. We also discussed design implications that might inform better tools that facilitate intermediate communication within data science teams.