Published March 31, 2025 | Version v1
Poster Open

Know what happened to your data — a toolset for fully reproducible data analysis

  • 1. ROR icon Leibniz Institute for Catalysis
  • 2. ROR icon University of Rostock
  • 3. ROR icon University of Freiburg

Description

Scientific insight rests on the published work of our predecessors.[1] In the digital age, we are confronted with an exponential growth of available data. Hence, appropriate data management is urgently needed and data need to be of sufficient quality and accompanied by relevant metadata. A necessary though often underrepresented prerequisite for data to contribute to science is a gapless record of their provenance. We therefore need tools that automatically record each step from the raw/primary data to their final shareable representation and take care of the respective metadata (i.e., documentation) of each step starting with the data acquisition. Here, we present both, a general framework for the reproducible analysis of spectroscopic data (ASpecD) [2] as well as two concrete packages based upon it and dedicated to working with continuous-wave (cwepr) [3] and time-resolved (trepr) [4] EPR data. Further available packages include NMRAspecds [5] for NMR spectra and FitPy [6] for fitting models (e.g., spectral simulations) to data. Parts of a larger infrastructure for reproducible research are formats for recording all relevant metadata during data acquisition [7] and a modular laboratory information and management system [8] including, i.a., an ELN [9], PIDs, and a repository for “warm” research data.

References

[1] I. Newton, letter to Robert Hooke, February 5th, 1676
[2] J. Popp, T. Biskup, ASpecD: A modular framework for the analysis of spectroscopic data focussing on
reproducibility and good scientific practice, Chem. Meth. 2022, 2, e202100097
[3] M. Schröder, T. Biskup, cwepr – a Python package for analysing cw-EPR data focussing on reproducibility
and simple usage, J. Magn. Reson. 2022, 335, 107140
[4] J. Popp, M. Schröder, T. Biskup, trepr Python package, doi:10.5281/zenodo.4897112
[5] M. Schröder, NMRAspecds Python package, doi:10.5281/zenodo.13293054
[6] T. Biskup, FitPy Python package, doi:10.5281/zenodo.5920380
[7] B. Paulus, T. Biskup, Towards more reproducible and FAIRer research data: documenting provenance
during data acquisition using the Infofile format, Digit. Discov. 2023, 2, 234
[8] T. Biskup, LabInform: A modular laboratory information system built from open source components,
ChemRxiv 2022, doi:10.26434/chemrxiv-2022-vz360
[9] M. Schröder, T. Biskup: LabInform ELN: A lightweight and flexible electronic laboratory notebook for
academic research based on the open-source software DokuWiki, ChemRxiv 2023,
doi:10.26434/chemrxiv-2023-2tvct

Files

Poster-Biskup-202503-ASpecD-EPR.pdf

Files (3.1 MB)

Name Size Download all
md5:fe45b29d593d278958a7d5ad258db4b6
3.1 MB Preview Download