VLDB attracts many submissions spanning diverse data management topics, and the PVLDB reviewing process is implemented by a large team of dedicated researchers. The Review Board of PVLDB Volume 14 consisted of 257 expert researchers, coordinated by 28 Associate Editors. Overall, we received 882 original manuscripts for PVLDB’s research track, of which ultimately 212 were accepted (for an acceptance rate of 24%) and have appeared in Issues 1–11 and 13 of PVLDB Volume 14. Issue 12 featured manuscripts of 56 accepted demonstrations, 22 industrial track papers, eight tutorials, three invited papers for the VLDB Endowment awards, and one panel abstract.

With PVLDB Volume 14 we initiated a new paper category, Scalable Data Science (SDS), to accept papers that describe the design, implementation, experience, and evaluation of solutions and systems for practical data science and data engineering tasks on large-scale data. These papers do not necessarily propose new breakthrough algorithms or models, but emphasize solutions that either solve or advance the understanding of issues related to data science technologies in the real world. In fact, one of these papers is among the ones selected for this special issue, namely the paper by Yuliang Li et al. describing the “Ditto” entity matching approach.

Overall, this special issue features four outstanding research papers published in PVLDB Vol 14 and presented at VLDB 2021 in Copenhagen. All papers have been significantly extended, revised, and re-reviewed for the special issue. Among them, the work “Scaling Attributed Network Embedding to Massive Graphs” by Yang et al. won the best paper award at VLDB 2021.

We are very grateful for all the great colleagues who contribute to the ongoing success of PVLDB and VLDB, including the authors, the reviewers, the management team, and the countless other individuals who volunteer their time to make the database community as vibrant and interesting as it is today.


Luna Dong and Felix Naumann

Editors-in-Chief of PVLDB volume 14 and PC-chairs of VLDB 2021