We solicit position papers for a special track at ICDE 2024. The field of databases is rapidly growing simultaneously in several ways. New systems with new capabilities and new approaches to data management are being constantly developed. Database technologies and ideas are finding their way into new applications. The field of data science, of which data curation, wrangling, cleaning, etc. are key is exploding. Over the years, we as a community have adapted our conferences to accommodate and encourage such growth. For instance, the CIDR conference targets early papers that provide a forum to exchange radically new ideas. Conferences such as VLDB and SIGMOD have created special tracks to promote research in data science and to provide a forum to share experiences dealing with data analysis in diverse application settings. The objective of ICDE 2024 DEFT Track is to look forward and provide visions for data engineering and analytics in the near future. The submissions must therefore provide well articulated problem statement and motivations to set the stage, solution space and possibly some preliminary studies. The papers may be speculative, not be perfect, but must be thought provoking, with basis on science and technology.

As in previous year, we will have a panel of distinguished special track PC members that consist of senior members of our community (listed below). The DEFT track submission offers an opportunity to share your vision of novel challenges faced by future data systems, novel use cases/applications of data management technologies in emerging areas. It also provides a unique opportunity to get feedback on your futuristic research from distinguished senior researchers in our community.

We welcome submissions in the following two categories. The categories listed below are not intended to be exhaustive. Papers that do not necessarily fall into one of these two categories will also be considered. However, papers that are suitable for research and data science tracks should NOT be submitted here.

• Vision Papers: Papers describing data management use cases/scenarios that push the limit of existing systems The papers should clearly articulate the importance of the use case, make an argument about limitations of existing technology, and lay out a direction of the future.
• Expanding the Landscape: Papers that highlight database technologies to be used in novel ways to solve problems in different domains (e.g., precision medicine using OLAP technology, data engineering for 3D scene construction and protein folding with data preparation techniques ). Novel applications about data, topics include but not limited to data pricing, data auction and data sharing, and data management issues in metaverse. Papers addressing any emerging novel data usage applications

Submission Length: 6-12 pages, double column, IEEE format. It is recommended that papers be closer to 6 pages than the maximum limit of 12.
Number of Submissions: Each person can co-author NO MORE than 2 submissions of which, he/she can be a lead author of at most one paper.
Submissions from DEFT Track PC: We encourage members of the DEFT track PC to consider submitting papers as well. Since the DEFT track PC list is small, to maintain anonymity of reviews further, for papers co-authored by DEFT track PC members, we may seek reviewers from regular PC as needed.
Submissions should be done to the Microsoft CMT at the following link: https://cmt3.research.microsoft.com/ICDEDEFT2024

• Submission due: October 2nd November 24, 2023
• Notification to authors (Accept/Reject): Jan 15 February 16th, 2024
• Camera-ready copy due: March 22, 2024

Beng Chin Ooi, NUS, Singapore

Alon Halevy, Meta
Anastasia Ailamaki, EPFL
AnHai Doan, University of Wisconsin-Madison
C. Mohan, Hong Kong Baptist University
Chris Jermaine, Rice University
Divesh Srivastava, AT\&T
Divyakant Agrawal, UC Santa Barbara
Fatma Ozcan, Google
Gustavo Alonzo, ETH
H. Jagadish, University of Michigan
Hank (Henry) Korth, Lehigh University
Jian Pei, Duke University
Michael J Carey, University of California, Irvine
Surajit Chaudhuri, Microsoft
Tamer Ozsu, Waterloo
Wang-Chiew Tan, Facebook AI