Scope of Topics
While we are interested in any submissions at the intersection of provenance and visualization, we are especially focused on:
- What can we learn when contrasting the problems of these two communities? Is there any visualization problem that can benefit from a database/analytic provenance method or vice versa?
- What are the most pressing provenance-related challenges in the database
community? Is there any visualization-related solution to them? For example,
How can query languages be supported from the standpoint of provenance and
- What visualization techniques may be used to assist the database community in constructing retrospective and prospective provenance that are more interactive, scalable, and user-friendly?
- How do we show changes to visualizations, interactions, or algorithms over time in various domains, including progressive visualizations, interactive visualizations, and machine learning training?
- How do we transparently and efficiently share visualizations and their production processes?
July 15, 2023: Paper submission deadline
August 3, 2023: Paper author notification
August 13, 2023: Paper camera-ready version deadline
Notice: all times are midnight Anywhere on Earth (AOE)
Notice: all times are Melbourne Time (GMT+11)
Introduction and Welcome
In this talk he will survey work at the intersection of provenance (in databases) and visualization. He will discuss how visualization techniques may be essential in overcoming challenges in data provenance / explanations such as how to effectively communicate complex and large provenance graphs. Furthermore, he will argue that provenance techniques can be utilized to overcome challenges in visualization. e.g., by enabling fast refresh of updated visualizations and for helping users to contextualize visualizations through understanding how a visualization was produced. Furthermore, he will cover some recent research on using approximate provenance to speed-up query answering that can potentially be applied when refreshing visualizations.
Bio: Boris Glavic is an Associate Professor in the Department of Computer Science at Illinois Institute of Technology leading the IIT DBGroup. His research spans several areas of database systems and data science including data provenance, data integration, query execution and optimization, uncertain data, and data curation. Boris strives to build systems that are based on solid theoretical foundations.
Coffee Break ☕
In visualization, provenance is widely used for action recovery, to document analysis processes, and to analyze user behavior. In this talk, however, he will focus on an exciting application of provenance: to bridge between code-based and interactive and visual data analysis. Code-based and interactive data analysis have different strengths and weaknesses. Some operations can be more easily executed in one than in the other. Interactive visualization tends to be more “natural” and easier to understand, but code-based analysis is typically more reproducible. While traditionally these two approaches can’t be easily combined, He’ll show how we can leverage provenance data to tackle these issues and design a truly integrated analysis environment.
Bio: Alexander Lex is an Associate Professor of Computer Science at the Scientific Computing and Imaging Institute and the Kahlert School of Computing at the University of Utah. He directs the Visualization Design Lab where he and his team develop visualization methods and systems to help solve today’s scientific problems. Recently he is working on visualization accessibility, visual misinformation, provenance and reproducibility, and user study infrastructure. He is the recipient of an NSF CAREER award and multiple best paper awards or best paper honorable mentions at IEEE VIS, ACM CHI, and other conferences. He also received a best dissertation award from his alma mater. He co-founded Datavisyn, a startup company developing VA solutions for the pharmaceutical industry.
Breakout Group Discussions
Workshop Wrap-up & Synthesis
We will accept research papers/extended abstracts or position papers. Your submission should be commensurate with the level of contribution but is required to be at least 2 pages (plus references). Papers must follow the IEEE VIS TVCG Journal submissions guidelines and be submitted through the Precision Conference System (PCS) . Your submission should be anonymized to facilitate a double-blind review between authors and the conference organizers. Accepted authors will be invited to post their work in an arXiv collection (which will not be considered archival). We are in contact with journals about the possibility of a special issue for the work accepted by this workshop.
Kai Xu University of Nottingham
Michelle Dowling Pacific Northwest National Laboratory
John Wenskovitch Pacific Northwest National Laboratory
Jeremy E. Block University of Florida
Yilin Xia University of Illinois Urbana-Champaign
Bertram Ludascher University of Illinois Urbana-Champaign
Age Chapman University of Southampton