VLDB 2023: Call for Contributions - Demonstrations
VLDB 2023 invites submissions for demo proposals on any topic of interest, broadly defined, to the data management community. Accepted demonstration papers will appear in the PVLDB proceedings. One of the demonstrations presented at the conference will be selected to receive a Best Demo Award.
Important Dates (All deadlines below are AOE.)
- Proposal submission deadline: March 31, 2023 11:59pm AoE
March 24, 2023 11:59pm AoE - Notification of acceptance: May 26, 2023
Demo Proposals
The proposal must describe the demonstrated system, and state the novelty and significance of the contribution to data management research, technologies, and/or its applications. The proposal should pay special attention to describing the exact demonstration scenarios for the given system. This should include how the audience will experience the demo, what kind of functionality is supported, user scenarios, interface and interaction options, etc. Proposals must be submitted in camera-ready format and limited to 4 pages, inclusive of ALL material.
Video Submissions
We specifically encourage the submission of a demonstration video (of up to 5 minutes, 50MB max. file size) together with your demonstration proposal via CMT. Both the demonstration proposal and the video will then be accessible by the reviewers. Your video should summarize your demonstration and also audio-visually highlight its most important aspects, such as the user interface, options for user interactions, the system setup, etc. The video should be submitted in MPEG/AVI/MP4 format and be playable by the common media players. Please note that you will need to first finish your demo proposal submission and then edit it to add the video as a supplementary file.
Conflicts
To minimize biases in the evaluation process, we use CMT's conflict management system, through which authors should flag conflicts with the Demo Program Committee members. All authors of a submission must declare conflicts on CMT prior to the submission deadline.
You have a conflict with X:
- If you and X have worked in the same university or company in the past two years, or will be doing so in the next six months on account of an accepted job offer. Different campuses do not count as the same university for this purpose -- UC Berkeley does not have a conflict with UC Santa Barbara.
- X has been a co-author of a paper with Y in the last 3 years, or of 4 (or more) papers in the last 10 years.
- X has been a collaborator within the past two years, as evidenced in a joint publication (subsumed by the stricter rule on co-authorship above), joint research project, or jointly organized event, or are collaborating now.
- If you are the PhD thesis advisor of X or vice versa, irrespective of how long ago this was.
- If X is a relative or close personal friend.
Submissions with undeclared conflicts or spurious conflicts will be DESK REJECTED. There will be NO exceptions to this rule.
Originality and Duplicate Submissions
Note that demonstration proposals must not have been published, or be under consideration for publication, at any other forum. Demonstration proposals should specifically focus on the genuine aspects of the described systems and the intended interaction with the audience; they should not be a short version of an existing conference paper (whether or not this may have been published elsewhere).
Demo Submission
Demonstration proposals must be submitted electronically, in PDF format, using CMT. When creating a new paper submission, you will be given the option to choose a track. Choose the "Demonstrations" track for your demo proposal. A respective option to upload the demonstration video will be made available.
Demo Track Chairs
Alekh Jindal, Microsoft Research
Carsten Binnig, TU Darmstadt
Jennie Rogers, Northwestern University
Demo Track PC Members
Alexander van Renen, Friedrich-Alexander-Universität Erlangen-Nürnberg
Amir Gilad, Duke University
Amit Somech, Bar-Ilan University
Andrew Crotty, Carnegie Mellon University
Avigdor Gal, Technion -- Israel Institute of Technology
Behrooz Omidvar-Tehrani, Amazon
Bin Cui, Peking University
Cong Yan, Microsoft research
El Kindi Rezig, MIT
Enzo Veltri, University of Basilicata
Gabriel Ghinita, Hamad Bin Khalifa University
Georgia Troullinou, FORTH-ICS
Harish Doraiswamy, Microsoft Research India
Hiroaki Shiokawa, University of Tsukuba
Jaroslaw Szlichta, York University and IBM CAS
Jialin Ding, AWS
Jiangwei Zhang, National University of Singapore
Ju Fan, Renmin University of China
Jyoti Leeka, Microsoft
Krishna Kantikiran Pasupuleti, Oracle
Leonard Ribeiro, Federal University of Goiás
Lihong He, IBM Almaden Research Center
Manisha Luthra, TU Darmstadt
Mayuresh Kunjir, Amazon AWS
Milos Nikolic, University of Edinburgh
Mourad OUZZANI, Qatar Computing Research Institute, HBKU
Nan Tang, Qatar Computing Research Institute, HBKU
Nantia Makrynioti, CWI and RelationalAI
Ramon Lawrence, UBC
Rebecca Taft, Cockroach Labs
Renata Borovica-Gajic, University of Melbourne
Roee Shraga, Technion - Israel Institute of Technology
Rong Zhu, Alibaba Group
Sainyam Galhotra, University of Chicago
Sang-Wook Kim, Hanyang University, Korea
Simon Razniewski, Max-Planck-Institut für Informatik, Germany
Subarna Chatterjee, Harvard University, USA
Subhadeep Sarkar, Boston University
Tiago de Melo, Universidade do Estado do Amazonas
Tiemo Bang, TU Darmstadt
Tsz Nam (Edison) Chan, Hong Kong Baptist University
Varun Pandey, TU Berlin
Venkatesh Emani, Microsoft
Verena Kantere, National Technical University of Athens, Greece
Y.C. Tay, National University of Singapore
Yaron Kanza, AT&T Labs-Research
Yingxia Shao, BUPT
Yiru Chen, Columbia University
Yiwen Zhu, Microsoft
Yuval Moskovitch, Ben Gurion University
Zainab Abbas, KTH Royal Institute of Technology
Zeyuan Shang, Einblick Analytics
Zheguang Zhao, TU Darmstadt
Zhi Yang, Peking University