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VisRecall

VisRecall

We 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.

The full dataset can be downloaded at: https://darus.uni-stuttgart.de/dataset.xhtml?persistentId=doi:10.18419/darus-2826.

Contact: Yao Wang,

The data is only to be used for non-commercial scientific purposes. If you use this dataset in a scientific publication, please cite the following paper:

  1. VisRecall: Quantifying Information Visualisation Recallability via Question Answering

    VisRecall: Quantifying Information Visualisation Recallability via Question Answering

    Yao Wang, Chuhan Jiao, Mihai Bâce, Andreas Bulling

    IEEE Transactions on Visualization and Computer Graphics (TVCG), 28 (12), pp. 4995-5005, 2022.

    Abstract Links BibTeX Project