This special issue features six outstanding research papers published in PVLDB Vol 13 (VLDB 2020). These papers have been significantly extended and revised.

The 46th International Conference on Very Large Data Bases (VLDB 2020), originally planned to be held in Tokyo, Japan, from August 31 to September 4, 2020, was successfully held for the same period as an online event due to the COVID-19 pandemic. It has been organized in such a way that people from any time zone could participate in the conference at a time convenient to them. VLDB 2020 attracted a record number of participants—over 5000 people registered to attend!

PVLDB Vol13 received 827 research paper submissions. These papers were reviewed by 18 associate editors, 186 review board members, 26 external reviewers who helped us when specialized expertise was required, as well as 133 additional reviewers who assisted the main reviewers. Everyone worked very hard from April 2019 to July 2020, not only to review and select papers but also to work with the authors to improve the quality of their papers. In the end, 207 papers were accepted by PVLDB Vol 13 (the acceptance rate was 25.03%).

We worked with the associate editors to select 10 outstanding papers from the accepted ones. These papers were presented to the Best Paper Selection Committee for their independent assessment. The committee members were Gustavo Alonso (ETH Zurich, Switzerland), Beng Chin Ooi (National University of Singapore, Singapore, Chair), Jignesh M. Patel (University of Wisconsin-Madison, USA), Wang-Chiew Tan (Megagon Labs, USA) and Meihui Zhang (Beijing Institute of Technology, China). Based on the recommendations from the committee, the authors of seven selected papers, including the three papers which received the Best Paper Award and two Runner-up Awards at PVLDB 2020, were invited to submit an extended version of their papers to this special issue. The reviewers for the manuscripts submitted to this journal were a mix of those who had originally reviewed the conference versions, as well as additional experts who reviewed only the extended submissions. Following The VLBD Journal reviewing process, the following six papers were accepted for publication in this special issue:

  • “Opportunities for Optimism in Contended Main-Memory Multicore Transactions” by Yihe Huang, William Qian, Eddie Kohler, Barbara Liskov and Liuba Shrira (VLDB 2020 Best Paper Award Winner).

  • “Pushing Data-Induced Predicates Through Joins in Big-Data Clusters” by Srikanth Kandula, Laurel Orr and Surajit Chaudhuri (VLDB 2020 Best Paper Runner-up Award Winner).

  • “Cross-chain Deals and Adversarial Commerce,” Maurice Herlihy, Barbara Liskov and Liuba Shrira

  • “Adaptive Algorithms for Crowd-Aided Categorization,” Yuanbing Li, Xian Wu, Yifei Jin, Jian Li, Guoliang Li, and Jianhua Feng

  • “PM-LSH: A Fast and Accurate In-Memory Framework for High-Dimensional Approximate NN and Closest Pair Search,” Bolong Zheng, Xi Zhao, Lianggui Weng, Nguyen Quoc Viet Hung, Hang Liu, and Christian S. Jensen

  • “Maximum and Top-k Diversified Biclique Search at Scale,” Bingqing Lyu, Lu Qin, Xuemin Lin, Ying Zhang, Zhengping Qian, and Jingren Zhou (VLDB 2020 Best Paper Runner-up Award Winner).

This special issue is our last official duty as the VLDB 2020 PC chairs/PVLDB Vol 13 Editors in Chief. We would like to take this opportunity to thank all the authors and the reviewers of the papers for both PVLDB Vol 13 and for this special issue, the members of the Best Paper Selection Committee and the associate editors of PVLDB Vol 13 for their tremendous effort without which it would not have been possible to have the great success of VDLB 2020 and this special issue. We are really privileged to have the opportunity to work with all of you for the last two years. Thank you!

Magdalena Balazinska, The University of Washington.

Xiaofang Zhou, The Hong Kong University of Science and Technology.

PVLDB Volume 13 Editors-in-Chief and

VLDB 2020 Program Committee Chairs.