{"url":"/dataset/visrecall","name":"VisRecall","full_name":null,"description_markdown":"Despite its importance for assessing the effectiveness of communicating information visually, fine-grained recallability of information visualisations has not been studied quantitatively so far.\r\n\r\nWe 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.\r\n\r\nThis dataset contains stimuli and collected participant data of VisRecall. The structure of the dataset is described in the README-File. If you are interested in related codes of the publication, please refer to the code repository in Metadata for Research Software.","description_withheld":null,"homepage":"https://darus.uni-stuttgart.de/dataset.xhtml?persistentId=doi:10.18419/darus-2826","introduced_date":"2022-06-21","introduced_date_note":null,"introduced_by":{"paper":null,"title":"VisRecall: Quantifying Information Visualisation Recallability via Question Answering","first_author":null,"url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["VisRecall"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}