Recent advances in electrophysiology enable simultaneous recording of hundreds of channels while capturing intricate behaviours. However, the resulting complex datasets are often underutilized due to insufficient solutions for data management and sharing. We address these obstacles within the EU-funded multi-lab collaboration In2PrimateBrains, which investigates brain networks in non-human primates. We build on a set of modular open-source tools, methods, and services (https://gin.g-node.org/In2PrimateBrains/DataWorkflow) to achieve workflows that balance standardization with adaptability.Metadata collection using the lightweight odML metadata format allows automated data annotation and context provision in a human- and machine-readable manner. Standardization is achieved by controlled terminologies and metadata schemas built upon existing community efforts, including BIDS, BEP032 and openMINDS.The common data representation offered by Neo is used to interface with the variety of data formats used in participating labs. Data storage in the NIX data format ensures accessibility and facilitates comprehensive data organization and integration of metadata.For data sharing, we use GIN, a collaborative data platform. GIN provides version control for research data, fine-grained access control, collaborative features, and data publication services.The datasets curated with this workflow are interoperable for further processing by generic analysis scripts, tools, and services. Our case study on multimodal data and metadata management in a multi-lab collaboration demonstrates the utilization of an open ecosystem of tools, methods, and services to achieve FAIR research data.Funding: EU H2020 MSCA-ITN In2PrimateBrains, grant No 956669.Figure: Data and metadata management workflow for a multi-lab collaboration.