Context This presentation was given online on 2026-04-29 as part of the Coffee Lecture Series organized by the Thuringian Competence Network for Research Data Management (https://forschungsdaten-thueringen.de/event/ordnerstruktur.html). Abstract It is essential for researchers to create findable, accessible, interoperable, and reusable (FAIR) data and metadata. To achieve this, effective research data management (RDM) is crucial — as increasingly acknowledged by policies and funders. FAIRness and good management of research (meta)data hinge upon being organised and documented in an understandable manner, which includes consciously storing files in a clear folder structure. It is a good idea to establish a sensible folder structure early in a project. However, little knowledge about upcoming needs and potential struggles often thwart especially junior researchers from deliberate planning. Here, ready-made templates can provide a standardized starting structure, saving time and resources that would usually be required to lay out and expand or restructure a folder structure as a (thesis) project unfolds. We recently developed* a folder structure template (FST) (github archive: DOI: 10.5281/zenodo.15835125) that comprehensively covers the storage needs of early career researchers in the life sciences beyond data production for a single work package; i.e., comprising space for administrative documents, presentations, etc. Additionally, the template is enriched with RDM best practice guidance and metadata recording prototypes to promote informed, sustainable RDM habits. This talk covers the basics of RDM — repetition never hurts — and presents our folder structure template and its features. It aims to encourage researchers, students, and PIs to talk about RDM, review their habits, and collectively shift academic culture towards more love for data. * Demerdash, Dockhorn, and Wilbrandt (2025) Data Organization Made Easy: Comprehensive Folder Structure Template for Early Career Life/Natural Science Researchers, Data Science Journal, 24(), p. 35. DOI: 10.5334/dsj-2025-035. Additional Information Learning Goals Know Research Data Management (RDM) goals and general considerations Know where to look for RDM tools, resources, and help Be aware of the Folder Structure Template (DOI: 10.5281/zenodo.15835125) Duration 23 min Target Audience (Life Science) researchers of all career stages Prerequisites None Upload Content File Description Format 2026-04-27_FST-Coffee_LinkList.pdf List of all links from the slides, grouped by talk section for quick reference. .pdf 2026-04-27_FST-Coffee_LinkList.pages List of all links from the slides, grouped by talk section for quick reference. Editable version. .pages (Pages) 2026-04-27_FST_TKFDMCoffee.key Slide deck. Editable version. .key (Keynote) 2026-04-27_FST_TKFDMCoffee_archive.pdf Slide deck. .pdf (PDF/A) 2026-04-29_FST-Coffee_video.mp4 Recording of the talk (slides and voice). 23 minutes. .mp4

Copyright Tidy data illustrations (slide 8) are from: Illustrations from the Openscapes blog Tidy Data for reproducibility, efficiency, and collaboration by Julia Lowndes and Allison Horst. The presentation includes an xkcd Comic by Randall Munroe (slide 10). The license for these can be found here: https://xkcd.com/license.html. The permanent link is https://xkcd.com/1360/. If not stated otherwise, illustrations were drawn by Jeanne Wilbrandt. Funding Version 1 of this presentation was devised and executed during an employment of Jeanne Wilbrandt by the Leibniz Institute on Aging – Fritz Lipmann Institute (leibniz-fli.de). Additional partial funding was provided by The German Network for Bioinformatics Infrastructure – de.NBI (denbi.de). Version 2 was updated and executed during an employment of Jeanne Wilbrandt by the University of Vienna (univie.ac.at/en/), in a project funded by the FFG (project nr. FO999929800).