Best Practices for Managing Data Annotation Projects

TL;DR

This paper consolidates best practices and practical wisdom from Bloomberg's experienced annotation project managers to improve data annotation management in machine learning projects.

Contribution

It provides a comprehensive set of guidelines and insights derived from real-world annotation projects at scale, tailored for practitioners.

Findings

Effective project management strategies for large-scale annotation.

Key challenges and solutions in data labeling processes.

Best practices for quality control and team coordination.

Abstract

Annotation is the labeling of data by human effort. Annotation is critical to modern machine learning, and Bloomberg has developed years of experience of annotation at scale. This report captures a wealth of wisdom for applied annotation projects, collected from more than 30 experienced annotation project managers in Bloomberg's Global Data department.