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A Lightweight File System Based Approach to Getting Data Ready for Data Management Solutions Cover

A Lightweight File System Based Approach to Getting Data Ready for Data Management Solutions

Open Access
|Apr 2025

Abstract

According to the FAIR (findability, accessibility, interoperability, and reusability) principles, scientific data should always be stored with machine-readable descriptive metadata. Existing solutions to store data with metadata, such as electronic lab notebooks (ELN), are often not readily available or not sufficiently generic for arbitrary experimental or computational results.

In this work, we present the open-source echemdb toolkit for creating and handling data and metadata. The toolkit is running entirely on the file system level using a file-based approach, which can be adopted and adapted locally on the individual user’s workstation. The approach facilitates integration with other tools in a FAIR data life cycle, avoiding a complicated server setup. This also makes the toolkit more accessible to the broader audience in the research sector since no understanding of more sophisticated database technologies is required.

We showcase several aspects and applications of the toolkit: automatic annotation of raw research data with human- and machine-readable metadata, data conversion into standardised frictionless Data Packages, and an API for exploring the data. We also illustrate the creation of a web framework displaying the data using example data from the research area of energy conversion and storage. The benefits of storing data with annotations already on the file system level are discussed.

Language: English
Submitted on: Nov 7, 2024
Accepted on: Mar 11, 2025
Published on: Apr 21, 2025
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2025 Albert K. Engstfeld, Johannes M. Hermann, Nicolas G. Hörmann, Julian Rüth, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.