Overview

Transformations in many fields are enabled by rapid advances in our ability to acquire and generate data. The bottleneck to discovery is now our ability to analyze and make sense of heterogeneous, noisy, streaming, and often massive datasets. Extracting knowledge or insights from this abundance of data lies at the heart of 21st-century discovery, which can be used to inform decisions, coordinate activities, optimize processes, improve products and services, as well as enhance productivity and innovation across a wide range of business and scientific problems.

Data science is the practice of deriving insights from data enabled by statistical modeling, computational methods, interactive visual analysis, and domain-driven problem-solving. Data science draws from methodology developed in such fields as applied mathematics, statistics, machine learning, data mining, data management, visualization, and HCI. It drives discoveries in business, economy, biology, medicine, environmental science, the physical sciences, the humanities and social sciences, and beyond.

Visualization is an integral part of data science, and essential to enable sophisticated analysis of data. After nine highly successful events, the tenth Symposium on Visualization in Data Science (VDS) will be held at IEEE VIS 2024.

Special Theme for VDS’24

This year, we have a special theme soliciting contributions concerning ‘Data Science in the Age of AI.’ We encourage authors to submit their work involving systems, techniques, studies, and theories relating to the relationship between AI and data science work. Unlike previous years, we also encourage the submission of position papers if they belong to the special theme. If you are submitting a position paper be sure to clearly state so in the abstract.

Submitting a short or long paper to VDS will give authors a chance to present at VDS at IEEE VIS 2024.

Contact & Registration

Please use vds@ieeevis.org to get in touch with us, or follow us on Twitter at @VisualDataSci.

Symposium Chair

• John Wenskovitch, Pacific Northwest National Laboratory

Paper Chairs

• Anamaria Crisan, Tableau Research

• Dylan Cashman, Brandeis University

Web/Tech Chair

• Saugat Pandey, Washington University in St. Louis

Steering Committee

• Adam Perer, Carnegie Mellon University

• Liang Gou, Bosch Research

• Alvitta Ottley, Washington University in St. Louis