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 onreproducibility 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 reproducibilityand 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 provenanceduring 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 foracademic research based on the open-source software DokuWiki, ChemRxiv 2023,doi:10.26434/chemrxiv-2023-2tvct