Data Narration for the People: Challenges and Opportunities

Abstract

Data narration is the process of telling stories with insights ex-tracted from data. It is an instance of data science [4] where the pipeline focuses on data collection and exploration, answering questions, structuring answers, and finally presenting them to stakeholders [16, 17]. This tutorial reviews the challenges and opportunities of the full and semi-automation of these steps. In doing so, it draws from the extensive literature in data narration, data exploration and data visualization. In particular, we point out key theoretical and practical contributions in each domain such as next-step recommendation and policy learning for data exploration, insight interestingness and evaluation frameworks, and the crafting of data stories for the people who will exploit them. We also identify topics that are still worth investigating, such as the inclusion of different stakeholders’ profiles in designing data pipelines with the goal of providing data narration for all.