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 eight highly successful events, the ninth Symposium on Visualization in Data Science (VDS) will be held at IEEE VIS 2023.
Submitting a short or long paper to VDS will give authors a chance to present at VDS at IEEE VIS 2023.
Contact & Registration
Please use email@example.com to get in touch with us, or follow us on Twitter at @VisualDataSci.
- Alvitta Ottley, Washington University, St. Louis
Vis Paper Chairs
Anamaria Crisan, Tableau Research
Michael Behrisch, Utrecht University, Netherlands
- Jorge Ono, Bosch Research
- Shayan Monadjemi, Washington University in St. Louis
Alexander Lex, University of Utah
Torsten Möller, University of Vienna
Adam Perer, Carnegie Mellon University
Liang Gou, Bosch Research (IEEE VIS liaison)