This repository contains supporting information for the manuscript denoted A Lightweight Approach to Getting Data Ready for Data Management Solutions. The manuscript illustrates how echemdb's toolbox can be used for local research data management. It provides information on file naming convention (FNC), automatic/programmatic metadata acquisition, and converting data into frictionless Data Packages. Furthermore, the unitpackages API is introduced (based on the frictionless Python framework), which allows creating, interacting, and exploring these Data Packages.
The examples from the manuscript and the usage of our tools for RDM applications are also illustrated in a specific documentation.
The doc folder contains Jupyter notebooks on
- how ro get started with local data management
- illustrating automatic annotation of metadata with watchdog
- providing usage examples for the unitpackage API
and a folder with
The required packages can be found in the environment.yml, which can be installed manually, with pip, or conda/mamba in a specific environment.
conda env create -f environment.ymlMore details on requirements and installation instructions can be found in the Getting started section.