Towards automating data narratives

Abstract

We propose a new area of research on automating data narratives. Data narratives are containers of information about computationally generated research findings. They have three major components: 1) A record of events, that describe a new result through a workflow and/or provenance of all the computations executed; 2) Persistent entries for key entities involved for data, software versions, and workflows; 3) A set of narrative accounts that are automatically generated human-consumable renderings of the record and entities and can be included in a paper. Different narrative accounts can be used for different audiences with different content and details, based on the level of interest or expertise of the reader. Data narratives can make science more transparent and reproducible, because they ensure that the text description of the computational experiment reflects with high fidelity what was actually done. Data narratives can be incorporated in papers, either in the methods section or as supplementary materials. We introduce DANA, a prototype that illustrates how to generate data narratives automatically, and describe the information it uses from the computational records. We also present a formative evaluation of our approach and discuss potential uses of automated data narratives.