Public Data Visualization: Analyzing Local Running Statistics on Situated Displays

Abstract

Popular sports tracking applications allow athletes to share and compare their personal performance data with others. Visualizing this data in relevant public settings can be beneficial in provoking novel types of opportunistic and communal sense-making. We investigated this premise by situating an analytical visualization of running performances on two touch-enabled public displays in proximity to a local community running trail. Using a rich mixed-method evaluation protocol during a three-week-long in-the-wild deployment, we captured its social and analytical impact across 235 distinct interaction sessions. Our results show how our public analytical visualization supported passers-by to create novel insights that were rather of casual nature. Several textual features that surrounded the visualization, such as titles that were framed as provocative hypotheses and predefined attention-grabbing data queries, sparked interest and social debate, while a narrative tutorial facilitated more analytical interaction patterns. Our detailed mixed-methods evaluation approach led to a set of actionable takeaways for public visualizations that allow novice audiences to engage with data analytical insights that have local relevance.