Demonstration Track of the
47th International Conference on Very Large Data Bases

August 16-20, 2021
Copenhagen, Denmark (and online)



VLDB 2021 invites submissions for software demonstration proposals on
any topic of interest, broadly defined, to the data management
community. Software demonstrations are accompanied by short papers which
will appear in the PVLDB proceedings upon acceptance. One of the
demonstrations presented at the conference will be selected to receive
the VLDB 2021 Best Demo Award.

Important Dates

-	Proposal submission deadline: March 12, 2021 (5 p.m. PST)
-	Notification of acceptance: May 7, 2021
-	Camera-ready copy due: June 11, 2021

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.
Formatting guidelines and document templates are available at

Video Submissions

Since VLDB 2021 will be held in a hybrid format (attendees will be
present in Copenhagen but will also be able to participate online only),
we require all accepted demonstrations to be accompanied by a video (of
up to 5 minutes, 100 MB max. file size). We would like to encourage
authors to already submit a (draft) video with their first CMT
submission. 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.

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).


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

- If you and X have collaborated recently, as evidenced in a joint
   publication or jointly organized event in the past two years, 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.

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

Please do not hesitate to approach the co-chairs with questions
regarding the VLDB 2021 Demo Track. We are looking forward to your

-	Torsten Grust (University of Tuebingen, Germany)

-	Guoliang Li (Tsinghua University, China)

-	Yuanyuan Tian (IBM Research ?Almaden, USA)

Demo Track PC Members

Alvin Cheung, University of California, Berkeley, USA
Anja Gruenheid, Google Inc., USA
Anna Fariha, University of Massachusetts Amherst, USA
Avrilia Floratou, Microsoft, USA
Chengliang Chai, Tsinghua University, China
Da Yan, University of Alabama at Birmingham, USA
Dong Xie, Penn State University, USA
Evangelia Sitaridi, Amazon Web Services, USA
Felix Schuhknecht, Johannes Gutenberg-University Mainz, Germany
Gao Cong, Nanyang Technological Univesity, Singapore
George Fletcher, Eindhoven University of Technology, Netherlands
Hongzhi Wang, Harbin Institute of Technology, China
Hua Lu, Roskilde University, Denmark
Ingo Müller, ETH Zürich, Switzerland
Jana Giceva, TU Munich, Germany
Jia Yu, Washington State University, Germany
Jianguo Wang, Purdue University, USA
Jiannan Wang, Simon Fraser University, Canada
Ju Fan, Renmin University of China, China
Kai Zeng, Alibaba Group, China
Khuzaima Daudjee, University of Waterloo, Canada
Knut Stolze, IBM, Germany
Laure Berti-Equille, IRD, France
Lei Cao, MIT, USA
Lukas Rupprecht, IBM Research - Almaden, USA
Manuel Rigger, ETH Zurich, Switzerland
Mark Raasveldt, CWI, Netherlands
Michael Gubanov, Florida State University, USA
Ning Wang, Beijing Jiaotong University, China
Qun Chen, Northwestern Polytechnical University, China
Shuai Ma, Beihang University, China
Silu Huang, Microsoft, USA
Tarique Siddiqui, Microsoft Research, USA
Umar Farooq Minhas, Microsoft Research, USA
Vasilis Efthymiou, IBM Research - Almaden, USA
Wenjie Zhang, University of New South Wales, Australia
Wenlei Xie, Facebook, USA
Xiao Qin, IBM Research, USA
Xiaokui Xiao, National University of Singapore, Singapore
Yeye He, Microsoft Research, USA
Yingjun Wu, Amazon Web Services, USA
Yongxin Tong, Beihang University, China
Zhifeng Bao, RMIT University, Australia