DMLR: Data-centric Machine Learning Research -- Past, Present and Future

TL;DR

This paper discusses the importance of community engagement and infrastructure in developing next-generation datasets to advance machine learning science, emphasizing collective efforts for sustainable progress.

Contribution

It highlights the role of community and infrastructure in creating and maintaining impactful datasets for future machine learning research.

Findings

Community engagement is vital for dataset development.

Infrastructure supports sustainable dataset creation.

Collective efforts can accelerate ML scientific progress.

Abstract

Drawing from discussions at the inaugural DMLR workshop at ICML 2023 and meetings prior, in this report we outline the relevance of community engagement and infrastructure development for the creation of next-generation public datasets that will advance machine learning science. We chart a path forward as a collective effort to sustain the creation and maintenance of these datasets and methods towards positive scientific, societal and business impact.