CC BY 4.0Hamann, TobiasTobiasHamannRobrecht, MichèleMichèleRobrechtWawer, Max LeoMax LeoWawerWerheid, Jonas MaximilianJonas MaximilianWerheidMoser, MarioMarioMoserGaldino, Marcos AlexandreMarcos AlexandreGaldinoAbdelrazeq, AnasAnasAbdelrazeqLachmayer, RolandRolandLachmayerSchmitt, Robert H.Robert H.Schmitt2025-09-102025-09-102024-06-20https://publica.fraunhofer.de/handle/publica/495085https://doi.org/10.24406/publica-536210.24406/publica-5362Research data management (RDM) has become increasingly significant, focusing on ensuring the most benefit from data creation. This especially applies within the engineering sciences, where many different sources generate big amounts of heterogeneous data. However, integrating RDM into day-to-day work is difficult. Thus, methods need to be defined to effectively and conveniently manage research data with increased complexity and diversity of subdisciplines. This article aims to provide clarity and structure in research processes integrating RDM, considering various models and viewpoints to present a research process for engineering sciences that is inherited from RDM processes. Therefore, interviews and workshops in different formats were used to gather insights about requirements in day-to-day work and research processes. As for further steps, the process will be evaluated on a later stage through a validation survey that will be taken into implementation for the Joint Assistant for Research in Versatile Engineering Sciences (Jarves).enEngineering researchResearch data managementData lifecycleFAIR dataResearch data management process600 Technik, Medizin, angewandte Wissenschaften::600 Technik600 Technik, Medizin, angewandte Wissenschaften::650 Management, Öffentlichkeitsarbeitpaper