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LOGS Python

Access your Research Data via Python API
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LOGS
LOGS Python on a laptop screen
LOGS Python on a laptop screen

About LOGS Python

LOGS provides a robust Python API that allows users to access, manipulate, and automate research data within the LOGS platform. This API enables LOGS to connect with third-party platforms to integrate data from various sources, automate workflows, and utilize the extensive Python ecosystem for advanced analysis and visualization.

From Academia? Get Started Immediately.

For single academic research groups, we offer discounts up to 50%.

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Python-Native Access
to LOGS Data
Access and work with datasets, metadata, and research records directly in Python
Workflow Automation
& Reporting
Build scripts to handle repetitive tasks and data processing pipelines
Designed for Scientists
& Power Users
No web development skills required, just Python

Features

Python-Based Data Analysis and Visualization

Leverage the Python ecosystem to extend and customize your research workflows. Use tools such as Jupyter Notebooks, Matplotlib, and other scientific Python libraries to analyze data, run custom scripts, and visualize complex data, all within an integrated workflow tailored for scientific research.

Integration with ELNs, LIMS, and Analysis Software

LOGS-Python supports seamless integration and data exchange with ELNs, LIMS, and analysis software, streamlining workflows, centralizing information, and supporting collaborative research by ensuring your data remains accessible and up-to-date across platforms.

Workflow Automation, Reporting, and Data Retrieval

Reduce manual effort by automating routine data management tasks. LOGS-Python enables users to generate reports, execute search queries, and build custom workflow automations for data processing and retrieval. By streamlining repetitive activities, researchers gain faster access to relevant information and can focus on analysis and decision-making.

Data Download, Processing, and Re-Upload

LOGS-Python allows users to retrieve datasets for external processing, perform custom analyses, and upload results back into LOGS. This approach maintains data continuity, preserves context and metadata, and enables the management of both raw and processed data within a single research environment.

Want to take LOGS for a test drive?

Get in touch with our team to schedule a personalized demonstration or evaluate LOGS using your own data and workflows.

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Webinars

Discovery of small molecules that target RNA. NMR is the method of choice.

Integrating Measurement Requests, Data Collection, and Data Distribution in One Platform

Join us as we dive into a common challenge faced by research facilities: managing the ever-growing mountain of measurement data. As a facility manager, you’re all too familiar with the constant juggling act of handling sample submissions, data collection, and distribution—all while trying to keep your workflows efficient and your focus on the science.
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Articles

Research Data

Goethe University Frankfurt Manages Research Data with LOGS

Case study on FAIR data management in an NMR facility
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Case Study_Virginia Tech

How Virginia Tech’s NMR Facility Turned Crisis Into Continuity with LOGS

When operations at Virginia Tech’s NMR lab were suddenly disrupted, continuity could have faltered. Instead, with LOGS in place, the team sustained seamless data delivery — proving that smart infrastructure ensures resilience, not just efficiency.
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