openBIS is an open-source, integrated data management platform that combines an Electronic Laboratory Notebook , Inventory Management System, and data storage solution. Developed by ETH Zurich's Scientific IT Services, it enables researchers to document daily experimental or computational work, store related raw and processed data, and link everything to materials, samples, and protocols within the lab inventory. This comprehensive system ensures safe data storage, provenance tracking, and compliance with FAIR data principles, facilitating data that is Findable, Accessible, Interoperable, and Reusable. Key Features and Functionality: - Inventory Management: Organize and track laboratory samples, materials, protocols, and equipment, creating a shared resource accessible to all lab members. - Electronic Laboratory Notebook : Document experiments, link them to inventory items, and maintain a comprehensive record of research activities. - Data Management: Store and manage all data related to lab experiments, including raw, processed, and analyzed data, as well as scripts and Jupyter notebooks. - BigDataLink Module: Utilize openBIS as a metadata repository for large datasets that cannot be conveniently moved, managing versions of large datasets on cloud and HPC storage. - Integrations for Data Analysis: Analyze data stored in openBIS using Jupyter or MATLAB, with APIs available for integration into workflow managers for large-scale analysis. - Import/Export Capabilities: Import and export data using Excel, and export full lab notebooks and inventory folders to Excel and PDF formats. - Access and Rights Management: Control user profiles and access privileges, ensuring secure and organized data management. - Audit Trail: Maintain a record of all modifications made to any entity in the system, ensuring data integrity and traceability. - Modularity: Extend existing functionalities or add new ones by writing custom plugins, allowing for tailored solutions to specific research needs. Primary Value and Problem Solved: openBIS addresses the critical need for efficient and compliant research data management. By integrating inventory management, ELN, and data storage into a single platform, it streamlines laboratory workflows, enhances collaboration, and ensures data integrity. Researchers can meet the increasing requirements from funding agencies, journals, and academic institutions to publish data according to FAIR principles, thereby promoting transparency and reproducibility in scientific research.