We're pleased to announce that one of our papers has been listed among other papers on the pVLDB Reproducibility site (https://vldb.org/pvldb/reproducibility), and will be highlighted at the upcoming VLDB Conference in 2024.
The paper details:
Title: Pollock: A Data Loading Benchmark
Authors: Gerardo Vitagliano, Mazhar Hameed, Lan Jiang, Lucas Reisener, Eugene Wu, Felix Naumann & the reproducibility submission was assisted by Tomic Riedel
Venue: PVLDB 16:(8), 2023
pVLDB's reproducibility effort is being developed in conjunction with SIGMOD's starting with pVLDB 2018. It has the goal of assisting in building a culture where sharing results, code, and scripts of database research is the norm rather than an exception.
You can find all the details about reproducing these results on our HPI page under https://hpi.de/naumann/projects/data-preparation/pollock.html and for the code repository check out https://github.com/HPI-Information-Systems/Pollock.