VLDB 2022: Call for Contributions - Tutorials

VLDB 2022 invites submissions for tutorial proposals on all topics of potential interest to the conference attendees. Tutorial proposals should cover state-of-the-art research, development, and applications in specific data management related areas, and stimulate and facilitate future work. Tutorials on interdisciplinary directions, bridging scientific research and applied communities, novel and fast-growing directions, and significant applications are highly encouraged. We encourage tutorials in areas that may be different from the usual VLDB mainstream, but still very much related to VLDB mission and objectives of managing big data. We also encourage tutorials that apply advanced Machine Learning techniques to solve data management problems, and will be directly inviting a small number of tutorials from neighboring scientific communities. Tutorials should be targeted for a broad audience, and they must focus neither excessively, nor exclusively, on the authors’ own work.

Important Dates

All deadlines below are 5 PM Pacific Time.

Submission Guidelines

Tutorial submissions must be submitted electronically, in pdf format, at the conference submission site: https://cmt3.research.microsoft.com/PVLDBv15_2022.

Submissions should be formatted using the PVLDB style templates, with a maximum length of 4 pages, inclusive of ALL material.

Proposals should include:

Accepted Tutorials

Presentation slides will be made available to VLDB 2022 participants and will be published on the VLDB website. We require the tutorial presenters to put online a webpage that provides links to all reasonably drafted slides and references before the conference starts, for publication at the conference website. A four-page extended abstract, with an overview including bibliographic references, will appear in PVLDB’s VLDB 2022 issue. The camera-ready format version should be an updated version of the original submission that addresses suggestions from the tutorial chairs and possibly other reviewers. Authors must agree to standard PVLDB copyright releases for the tutorial abstract overview as well as for their slides. Authors will retain the rights to reuse all their material in any form. If the proposal is accepted, the program committee will discuss with authors potential ways for delivery, given the hybrid structure of the conference.

Please identify any other venues in which all or part of the tutorial has been or will be presented, and include an explanation of how the tutorial proposal for VLDB 2022 differs from these previous or forthcoming editions.

Identify topically related tutorials by other people in major data-centric research venues in recent years and contrast with their content and coverage.

Tutorial Chairs

Laks V.S. Lakshmanan, University of British Columbia
Yoshiharu Ishikawa, Nagoya University