Lost Data in Electron Microscopy

TL;DR

This study quantifies the significant amount of electron microscopy data that remains unused in publications, highlighting both a shortcoming in data utilization and an opportunity for data science and AI development.

Contribution

It provides the first large-scale estimate of data loss in electron microscopy and discusses strategies to leverage the unused data for scientific advancement.

Findings

Over 90% of electron microscopy data remains unpublished.

Only about 2% of generated images are used in peer-reviewed articles.

Large pool of unused data can be harnessed for AI and data science applications.

Abstract

The goal of this study is to estimate the amount of lost data in electron microscopy and to analyze the extent to which experimentally acquired images are utilized in peer-reviewed scientific publications. Analysis of the number of images taken on electron microscopes at a core user facility and the number of images subsequently included in peer-reviewed scientific journals revealed low efficiency of data utilization. Up to around 90% of electron microscopy data generated during routine instrument operation remain unused. Of the more than 150 000 electron microscopy images evaluated in this study, only approximately 3 500 (just over 2%) were made available in publications. For the analyzed dataset, the amount of lost data in electron microscopy can be estimated as >90% (in terms of data being recorded but not being published in peer-reviewed literature). On the one hand, these results highlight a shortcoming in the optimal use of microscopy images; on the other hand, they indicate the existence of a large pool of electron microscopy data that can facilitate research in data science and the development of AI-based projects. The considerations important to unlock the potential of lost data are discussed in the present article.