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 seventh highly successful events, the eighth Symposium on Visualization in Data Science (VDS) will be held at a new venue, ACM KDD 2022 as well as IEEE VIS 2022. VDS@KDD will be virtual and VDS@VIS will be hybrid (both virtual and in-person) in 2022. VDS will bring together domain scientists and methods researchers (including data mining, visualization, usability and HCI, data management, statistics, machine learning, and software engineering) to discuss common interests, talk about practical issues, and identify open research problems in visualization in data science.
Submitting a short or long paper to VDS will give authors a chance to present at VDS events at both ACM KDD 2022(virtual) and IEEE VIS 2022( hybrid). We hope this will help bring the communities of data mining and visualization more closely connected.
Contact & Registration
Vis Paper Chairs
KDD Paper Chairs
Junming Shao, University of Electronic Science and Technology of China
Nina Chritine Hubig, Clemson University
- Jorge Ono, Bosch Research
- Jen Rogers, University of Utah