VIS30K: A Collection of Figures and Tables from IEEE Visualization Conference Publications

TL;DR

VIS30K is a comprehensive dataset of nearly 30,000 figures and tables from three decades of IEEE Visualization conference papers, enabling analysis of the field's evolution and supporting research discovery.

Contribution

The paper introduces VIS30K, a large, curated dataset of visualization figures and tables, along with a web tool for searching and exploring the data, created through a semi-automatic CNN-based collection process.

Findings

Dataset covers 30 years of visualization research.

Semi-automatic collection ensures high-quality, comprehensive data.

Web-based tool facilitates efficient exploration of the dataset.

Abstract

We present the VIS30K dataset, a collection of 29,689 images that represents 30 years of figures and tables from each track of the IEEE Visualization conference series (Vis, SciVis, InfoVis, VAST). VIS30K's comprehensive coverage of the scientific literature in visualization not only reflects the progress of the field but also enables researchers to study the evolution of the state-of-the-art and to find relevant work based on graphical content. We describe the dataset and our semi-automatic collection process, which couples convolutional neural networks (CNN) with curation. Extracting figures and tables semi-automatically allows us to verify that no images are overlooked or extracted erroneously. To improve quality further, we engaged in a peer-search process for high-quality figures from early IEEE Visualization papers. With the resulting data, we also contribute VISImageNavigator (VIN, visimagenavigator.github.io), a web-based tool that facilitates searching and exploring VIS30K by author names, paper keywords, title and abstract, and years.