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Tue, 1 Jun 2021 16:28:45 +0000
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Call For Participation: Workshop on Provenance and Visualization (ProvViz)

21 July 2021

(Part of the Provenance Week 2021 - fully online)

https://iitdbgroup.github.io/ProvenanceWeek2021/provviz.html

The aim of this workshop is to encourage exchange between the provenance and visualization communities. During the workshop, we will introduce the latest developments in provenance analysis from the visualization community, and try to address research challenges that are relevant for both communities. It is part of Provenance Week 2021, which is a fully online event.

All Provenance Week 2021 participants are welcome to join. There is an option to submit a one-page abstract before the workshop if you would like to propose a topic or research question to be discussed at the workshop.

- Abstract Submission deadline: June 8th, 2021
- Author Notification: June 22nd, 2021

The LNCS format is recommended and please select the "ProvViz" track (which will be set up soon) when submitting the abstract in EasyChair (https://easychair.org/conferences/?conf=pw2021)

The workshop lasts half a day (morning of 21 July 2021), and will start with a keynote by Bill Howe (please see the information below). After that, participants will form groups to discuss a particular area or research question based on their shared interest. Finally, each group will report back their discussion results and collaboration plan after the workshop.

Keynote from Bill Howe, University of Washington

Bio: Bill Howe is Associate Professor in the Information School and Adjunct Associate Professor in the Allen School of Computer Science & Engineering and the Department of Electrical Engineering. His research interests are in data management, machine learning, and visualization, particularly as applied in the physical and social sciences. As Founding Associate Director of the UW eScience Institute, Dr. Howe played a leadership role in the Moore-Sloan Data Science Environment program through a $32.8 million grant awarded jointly to UW, NYU, and UC Berkeley, and founded UW’s Data Science for Social Good Program. With support from the MacArthur Foundation, NSF, and Microsoft, Howe directs UW’s participation in the Cascadia Urban Analytics Cooperative. He founded the UW Data Science Masters Degree, serving as its inaugural Program Chair, and created a first MOOC on data science that attracted over 200,000 students. His research has been featured in the Economist and Nature News, and he has authored award-winning papers in conferences across data management, machine learning, and visualization. He has a Ph.D. in Computer Science from Portland State University and a Bachelor’s degree in Industrial & Systems Engineering from Georgia Tech.

Regards,


Workshop Organizers

Eli T. Brown (DePaul University)
Marc Streit (Johannes Kepler University Linz)
John Wenskovitch (Virginia Tech)
Kai Xu (Middlesex University)


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