VIS30K: A Collection of Figures and Tables from IEEE Visualization Conference Publications
This dataset provides a comprehensive resource for visualization researchers to study the historical evolution of the field and discover relevant work based on graphical content. It is an incremental contribution for the visualization community.
The authors introduce VIS30K, a dataset comprising 29,689 figures and tables extracted from 30 years of IEEE Visualization conference publications. This dataset was created using a semi-automatic process combining convolutional neural networks with human curation, and is accompanied by a web-based exploration tool called VISImageNavigator.
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.