English

DMOps: Data Management Operation and Recipes

Databases 2023-06-27 v3 Machine Learning Methodology

Abstract

Data-centric AI has shed light on the significance of data within the machine learning (ML) pipeline. Recognizing its significance, academia, industry, and government departments have suggested various NLP data research initiatives. While the ability to utilize existing data is essential, the ability to build a dataset has become more critical than ever, especially in the industry. In consideration of this trend, we propose a "Data Management Operations and Recipes" to guide the industry in optimizing the building of datasets for NLP products. This paper presents the concept of DMOps which is derived from real-world experiences with NLP data management and aims to streamline data operations by offering a baseline.

Keywords

Cite

@article{arxiv.2301.01228,
  title  = {DMOps: Data Management Operation and Recipes},
  author = {Eujeong Choi and Chanjun Park},
  journal= {arXiv preprint arXiv:2301.01228},
  year   = {2023}
}

Comments

Accepted for Data-centric Machine Learning Research (DMLR) Workshop at ICML 2023

R2 v1 2026-06-28T08:01:14.220Z