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Related Experiment Video

Updated: May 7, 2026

Neurovascular Network Explorer 2.0: A Simple Tool for Exploring and Sharing a Database of Optogenetically-evoked Vasomotion in Mouse Cortex In Vivo

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An open-source data storage and visualization back end for experimental data.

Kenneth Nielsen¹, Thomas Andersen, Robert Jensen

¹1Center for Individual Nanoparticle Functionality (CINF), Department of Physics, Technical University of Denmark, Kgs. Lyngby, Denmark.

Journal of Laboratory Automation

|September 25, 2013

Summary

This summary is machine-generated.

This study introduces a flexible, open-source software system for laboratory data logging and presentation. It offers centralized storage, live data visualization, and enhanced experimental monitoring for improved efficiency and reliability.

Keywords:

PHP Python collaboration database experimental data logging open source storage visualization

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Area of Science:

Laboratory Automation
Scientific Data Management

Background:

Laboratories require robust systems for continuous and ad hoc data collection.
Centralized data storage and visualization are crucial for efficient experimental monitoring and management.

Purpose of the Study:

To describe a flexible, free, and open-source software system for laboratory data logging and presentation.
To enable centralized data storage and live visualization for enhanced experimental oversight.

Main Methods:

Development of a modular software system comprising data-logging clients, a data server, and a web-based presentation interface.
Implementation of resilient data logging from independent clients with central data storage.
Creation of a visualization front end for live data monitoring on web-enabled devices.

Main Results:

The system provides a highly adaptable solution for centralized data storage and retrieval.
Live data visualization allows real-time monitoring of experiments, facilitating timely adjustments.
Centralized storage simplifies data backup and exchange, enhancing data integrity and accessibility.

Conclusions:

The described software system offers a resilient and adaptable solution for laboratory data management.
Live visualization and system parameter logging enable advanced automation and surveillance features.
This open-source system can be broadly applied in any laboratory setting requiring efficient data logging and presentation.