ACM SIGMOD “Best Artifact” Award

The ACM SIGMOD Best Artifact Award recognizes the best papers in terms of reproducibility. Up to three comprehensively reproduced papers are carefully selected and the awards are presented during the awards session of the SIGMOD conference (next year). Each award comes with a $750 honorarium. The criteria for the award broadly include: (i) coverage, (ii) ease of reproducibility, (iii) flexibility, and (iv) portability.

Specifically, the award recognizes reproducible papers that did the extra mile and provided artifacts that are fully and easily reproducible and offer increased flexibility (being able to add workloads, queries, data and exhibiting similar behavior with published results) and portability (ideally, portable to more than one operating systems and across versions)

Winners of 2024

Awarded to Best Artifact(s) of ACM SIGMOD 2023.

Awards Chair: Dennis Shasha

Best Artifact

InfiniFilter: Expanding Filters to Infinity and Beyond

by Niv Dayan (University of Toronto), Ioana Bercea (IT University of Copenhagen), Pedro Reviriego (Universidad Politecnica de Madrid), Rasmus Pagh (University of Copenhagen, Copenhagen)

Honorable Mentions

DeltaBoost: Gradient Boosting Decision Trees with Efficient Machine Unlearning

by Zhaomin Wu (National University of Singapore), Junhui Zhu (National University of Singapore), Qinbin Li (National University of Singapore), Bingsheng He (National University of Singapore)

A Step Toward Deep Online Aggregation

by Nikhil Sheoran (Databricks & University of Illinois at Urbana-Champaign), Supawit Chockchowwat (University of Illinois at Urbana-Champaign), Arav Chheda (University of Illinois at Urbana-Champaign), Suwen Wang (University of Illinois at Urbana-Champaign), Riya Verma (University of Illinois at Urbana-Champaign), Yongjoo Park (University of Illinois at Urbana-Champaign)

Winners of 2023

Awarded to Best Artifact(s) of ACM SIGMOD 2022.

Awards Committee: Dennis Shasha (chair), Asterios Katsifodimos, Torsten Grust, Juan Lastra-Díaz

Best Artifact

JEDI: These aren’t the JSON documents you’re looking for…

by Thomas Hütter (University of Salzburg), Nikolaus Augsten (University of Salzburg), Christoph M. Kirsch (University of Salzburg & Czech Technical University), Michael J. Carey (University of California, Irvine), Chen Li (University of California, Irvine)
Verified by: Torsten Grust, Universität Tübingen

Honorable Mention

HypeR: Hypothetical Reasoning With What-If and How-To Queries Using a Probabilistic Causal Approach

by Sainyam Galhotra (University of Chicago), Amir Gilad (Duke University), Sudeepa Roy (Duke University), Babak Salimi (University of California, San Diego)
Verified by: Yuxin Tang, Rice University

Winners of 2022

Awarded to the most Comprehensively Reproduced Paper of ACM SIGMOD 2021.

Conformance Constraint Discovery: Measuring Trust in Data-Driven Systems

by Anna Fariha (University of Massachusetts), Ashish Tiwari (Microsoft), Arjun Radhakrishna (Microsoft), Sumit Gulwani (Microsoft), Alexandra Meliou (University of Massachusetts)
Verified by: Maria Daltayanni, University of San Francisco

Winners of 2021

Awarded to Most Reproducible Papers of ACM SIGMOD 2020.

Functional-Style SQL UDFs With a Capital ‘F’

by Christian Duta, Torsten Grust
Verified by: Dmytro Bogatov, Boston University

Factorized Graph Representations for Semi-Supervised Learning from Sparse Data

by Krishna Kumar P., Paul Langton, Wolfgang Gatterbauer
Verified by: Asterios Katsifodimos, TU Delft

QueryVis: Logic-based Diagrams help Users Understand Complicated SQL Queries Faster

by Aristotelis Leventidis, Jiahui Zhang, Cody Dunne, Wolfgang Gatterbauer, H.V. Jagadish, Mirek Riedewald
Verified by: Raul Castro Fernandez, The University of Chicago

Winners of 2020

Awarded to Most Reproducible Papers of ACM SIGMOD 2019.

Raha: A Configuration-Free Error Detection System

by Mohammad Mahdavi, Ziawasch Abedjan, Raul Castro Fernandez, Samuel Madden, Mourad Ouzzani, Michael Stonebraker, Nan Tang
Verified by: Subarna Chatterjee, Harvard University

Uncertainty Annotated Databases – A Lightweight Approach for Approximating Certain Answers

by Su Feng, Aaron Huber, Boris Glavic, Oliver Kennedy
Verified by: Siqiang Luo, Harvard University

Winners of 2019

Awarded to Most Reproducible Papers of ACM SIGMOD 2018.

Randomized Algorithms Accelerated over CPU-GPU for Ultra-High Dimensional Similarity Search

by Yiqiu Wang, Anshumali Shrivastava, Jonathan Wang, Junghee Ryu
Verified by: Manos Athanassoulis and Subhadeep Sarkar, Boston University

Adaptive Optimization of Very Large Join Queries

by Thomas Neumann, Bernhard Radke
Verified by: Wilson Qin and Abdul Wasay, Harvard University

Robust Entity Resolution using Random Graphs

by Sainyam Galhotra, Donatella Firmani, Barna Saha, Divesh Srivastava
Verified by: Wilson Qin and Abdul Wasay, Harvard University

Winners of 2018

Awarded to Most Reproducible Papers of ACM SIGMOD 2017.

Transaction Repair for Multi-Version Concurrency Control

by Mohammad Dashti (EPFL), Sachin Basil John (EPFL), Amir Shaikhha (EPFL), Christoph Koch (EPFL)
Verified by: Stratos Idreos, Abdul Wasay and Wilson Qin, Harvard University

Data Canopy: Accelerating Exploratory Statistical Analysis

by Abdul Wasay (Harvard), Xinding Wei (Harvard), Niv Dayan (Harvard), Stratos Idreos (Harvard)
Verified by: Peter Triantafillou, University of Glasgow

Debunking the Myths of Influence Maximization: An In-Depth Benchmarking Study

by Akhil Arora (Xerox Research Centre India), Sainyam Galhotra (University of Massachusetts, Amherst), Sayan Ranu (Indian Institute of Technology, Delhi)
Verified by: Dan Olteanu, Oxford