Nowadays, there is a widespread movement towards Open Science and Open Research Data (ORD),[1] which must adhere to the FAIR data principles (Findable, Accessible, Interoperable, and Reusable).[2] This entails that data need to be described by rich metadata, stored in open and machine-readable formats, and made accessible through standardized, open protocols. The amount of data generated in academic research labs is growing exponentially due to rapid technological and scientific advances. Without appropriate systems and procedures in place, managing, organizing, and sharing these data becomes increasingly difficult and inefficient. Research Data Management (RDM) plays a crucial role in addressing these challenges throughout the entire data lifecycle—from data creation and processing, to storage, sharing, and preservation. Good RDM practices are prerequisite for FAIR and Open Research Data, ensuring data integrity, reproducibility of research findings, and long-term usability of data. In this context, tools such as Electronic Laboratory Notebooks (ELN), Laboratory Information Management Systems (LIMS) and management platforms for active research data can help experimental scientists in managing their data more effectively. Such tools can be used to track samples, materials, equipment, standard operating procedures (SOPs), experimental measurements, as well as raw and result data, thus covering the full data life cycle. However, such systems are often complex and their introduction in academic research labs can present challenges, due primarily to the need for scientists to adapt to new workflows and tools, which may differ considerably from traditional lab practices. Additionally, there is often an initial learning curve associated with using ELNs and/or LIMS effectively. To facilitate smoother adoption and ensure successful long-term integration, dedicated support from RDM specialists is essential. The Scientific IT Services (SIS) unit of ETH Zurich develops openBIS, an open-source data management platform with an integrated ELN and LIMS. [3],[4] SIS provides RDM services to experimental scientists at ETH Zurich and beyond based on the openBIS platform. These include software provisioning and maintenance, trainings and support for customization of the software to the needs of the lab, regular user support. Introducing a data management system with ELN/LIMS capabilities in an academic lab should be approached as a project, typically consisting of three phases: 1. Introduction: 1 or 2 people in the lab are appointed to drive the project and the needs of the lab are identified. 2. Pilot: the software is customized to the needs of the lab and a few selected people in the lab test it. 3. Production: if the pilot is successful, every lab member starts using the system. Further customization can be done at this stage. The length of the entire process varies significantly depending on the degree of customization and the specific needs and complexity of the laboratory, ranging from a few weeks to several months. In our experience, three key factors are necessary for a successful outcome: 1. Commitment of lab head; 2. Commitment of appointed lab members driving the project; 3. Support from RDM specialists. In this talk, we will share insights gained over the last years providing openBIS-based RDM services at ETH Zurich and other Swiss and European academic institutions.