LOGS

LOGS is a scientific data exchange platform designed for research teams and measurement facilities to collect, manage, and share research data in accordance with FAIR data principles. It provides a powerful Scientific Data Management System (SDMS) that supports the complete research data lifecycle, from data acquisition and organization to secure sharing and reuse, It also includes an integrated Notebook, a flexible and powerful lab Inventory system and Python functionalities (Python-API) to streamline the way you handle research data.

LOGS can be deployed on‑premise or in the cloud and integrates data, metadata, and experimental documentation into a single, browser‑based platform, enabling efficient collaboration and long‑term data preservation.

Centralized Data Access from Anywhere: All research data is stored in one system, allowing researchers to instantly find and use information without searching across multiple tools or losing time retrieving files.

Data Reusability and FAIR Compliance: Data is captured together with metadata, ensuring experiments remain findable, reproducible, and reusable while supporting FAIR data requirements.

Elimination of Manual Data Handling: Automatic data capture from instruments removes manual uploads, ensuring datasets are complete, consistent, and free from human error.

Faster Data Analysis and Decision-Making: Built-in search, visualization, and filtering tools enable researchers to interpret results directly within the platform, accelerating insights without relying on external software.

Seamless Collaboration and Data Sharing: Secure, browser-based access and integrations with ELNs, LIMS, and external systems enable teams to work on the same data, improving collaboration and eliminating duplication.

Streamlined Laboratory and Facility Workflows: Data, experiments, inventory, and facility operations are managed in one environment, improving efficiency and providing greater control over research processes.