provides important insights into the chemical reactivity and electrochemical properties of the analyzed compounds. Cyclic voltammetry is a standard technique in chemistry, materials sciences 23 and has also relevance for biological applications. We elaborated a comprehensive example for a "FAIRer" processing of research data using cyclic voltammetry (CV) measurements, as this analytical method combines different challenges that complicate a comprehensive FAIR data compliant workflow. Solving these challenges and presenting solutions for CV shows how powerful the new developments are and how they can be transferred and applied to other experiment and analysis techniques. The current challenges for FAIR data compliant cyclic voltammetry data collection are missing standards for the measured data and its metadata, the quite diverse equipment that is used for the measurements, such as different potentiostats and electrodes, and the representation of the results as cyclic graphs with several repetitive measurements that describe one experiment. For transparency and complete reproducibility, the CV measurements should be described using the data generated by the device, including metadata automatically provided by the potentiostat and additional information provided by the user. The values and parameters that characterize the measurements and are not recorded in the digital output file of the potentiostat are also included. Well known vendors for cyclic voltammetry equipment are, for example, Metrohm, Gamry and PalmSens. All three manufacturers use their own data format which complicates standardization, readability and reusability of the data and metadata without the use of additional data management software. Usually, the vendor's software supports the export as text file or as CSV, but export formats and metadata included are not standardized amongst the vendors. In some cases, the converted files are also missing important metadata. In order to establish a workflow for FAIR cyclic voltammetry measurements, we elaborated a process that can be applied to the devices and software of the vendors presented herein and can easily be adapted to other vendors' devices. Our process can be described in five parts which together describe how to generate annotated CV measurements in an open and standardized format, including cases where the original data files are produced by different devices and possibly in different (proprietary) file formats. In the first step, the data is transferred to a digital work or documentation environment which, in our case, is the Chemotion ELN (Figure , step 1). After the data has been received by the ELN, an automated reader can process the data by applying file format and vendor specific profiles to convert the data files to a standardized format. In parallel, the available metadata are extracted from the transferred file and mapped to a predefined metadata scheme. The converted data and metadata are then combined in a BagIt-container (Figure , step 2). The data now contained in the BagIt container can then be plotted, analyzed and annotated as a digital graph in the GUI of the ELN. The analyzed and annotated data and all further documented metadata and their changes are then saved in additional files (Figure , step 3), retaining an unaltered copy of the original data. As the ELN supports the sustainable re-use of the data captured, data and metadata can be transferred to an open access repository or can be downloaded with the full support of data and metadata (Figure , step 4). The described workflow towards FAIR data in CV should be re-usable by other scientists without limitations, therefore all methods and software that were used for the establishment of the workflow are available as open source. Step 1: Transfer of data from devices to an ELN: Data recorded during a CV experiment using a vendor's software is usually saved locally to the instrument's computer. Fetching the data from that computer involves manual transfer to a physical data storage device, such as a USB drive, or (automatically) copying it to a remote storage location, from which the researcher can access it for further analysis. In order to allow systematic access to data of cyclic voltammetry experiments, we established a routine that automatically transfers the data from the device's PC to the ELN. The routine is explained using a Gamry potentiostat with the vendor's original, unchanged software, "Gamry Framework". The process was also applied to potentiostats from Metrohm and PalmSens (details described in SI). The workflow for such a routine is composed of data recording and storing on the local hard drive, the transfer from the hard drive to a remote storage and the transfer from that storage location to the ELN. In preparation for the data transfer, several points have to be clarified. This includes information on the location the data is saved to on the computer, information on the supported data format(s) and type(s) (is the data stored in folders, single files or as multiple files?), and information on how the data is recorded. The last point is important as some devices write continuously to an initially created file and therefore induce continuously growing file sizes, others create just one data file at the end of the experiment and cache the data until the experiment is complete. In the case of the herein depicted example of a Gamry device, the data file generation is started with the data acquisition and data is written to this file during the experiment. The data file can be assumed to be complete when the data file is closed and no further changes/increase of data content is observed (information on the process for Metrohm and PalmSens can be gained from the SI).