DODA: Introducing A Database of Datasets for Aesthetics
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Stimulus selection is a critical first step in the empirical and computational investigation of vision and art. While many image and stimulus sets have been curated and published alongside valuable data, it can be difficult to find the best set for one’s own research, as they often differ in various aspects and are shared across different platforms. Therefore, we present a Database of Datasets for Aesthetics (DODA), an intuitive Web Application in which researchers can browse all important datasets for aesthetics research, with annotated properties that are highly relevant for their possible suitability. Based on a systematic review of stimulus sets in aesthetics, DODA offers a centralized search system, intended to promote open-science oriented research practices. Currently, DODA encompasses over 50 datasets, with a link to their location on the web. We compare the datasets and document relevant selection criteria, such as Size, Number of Participants, Participants per Stimulus, Research Question, Rating Scales, Stimulus Source, Resolution, Homogeneity, etc. The information is displayed in a table for users to easily filter through, prioritizing the criteria most important to them. DODA also provides a wide range of quantitative image properties (QIPs) computed for all datasets for users to download. Reusing a dataset is not only ecological for the researcher and environment, but it also allows for the comparison of different variables across the same stimulus set, increasing our collective understanding of aesthetic appreciation. Working on the same datasets provides a feasible opportunity to directly and indirectly collaborate across methodologies within aesthetics. For DODA to grow alongside the field of aesthetics, we encourage researchers to suggest other aesthetics datasets to be included in the future. DODA is part of the Aesthetics Toolbox, which encompasses useful tools like image resizing and calculating QIPs to make aesthetics research on digital stimuli more accessible and reproducible Acknowledgment: This work is funded by an ERC Advanced Grant (No. 101053925) awarded to JW.
Recommended citation: Koßmann, L., Bartho, R., Redies, C. & Wagemans, J. (2025). DODA: Introducing A Database of Datasets for Aesthetics [Poster]. Visual Science of Art Conference (VSAC), Wiesbaden, Germany.