Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"

We propose a question-answering paradigm to study visualisation recallability and present VisRecall -- a novel dataset consisting of 200 information visualisations that are annotated with crowd-sourced human (N = 305) recallability scores obtained from 1,000 questions from five question types, which are related to titles, filtering information, finding extrema, retrieving values, and understanding visualisations.

It aims to make fundamental contributions towards a new generation of methods to assist designers in optimising information visualisations. This dataset contains stimuli and collected participant data of VisRecall. The structure of the dataset is described in the README-File.