This resource ("Resource") provides an efficient approach for neuroscience labs to create and manage scientific data workflows: the complex multi-step methods for data collection, preparation, processing, analysis, and modeling that researchers must perform in the course of an experimental study. The work is derived from the developments in leading neuroscience projects and uses the DataJoint framework for defining, deploying, and sharing their data workflows.
An overview of the principles of DataJoint workflows and the goals of DataJoint Elements are described in the position paper "DataJoint Elements: Data Workflows for Neurophysiology".
The Resource provides the following main components:
the open-source framework for data pipelines and automated computational workflows + related documentation, tools, and utilities.
a collection of curated modules for assembling workflows for the major modalities of neurophysiology experiments + related documentation, tools, and utilities.
- Lab management
- Animal management
- Experiment session
- Extracellular array electrophysiology
- Calcium imaging
- Miniscope imaging
The DataJoint framework
- DataJoint for Python
- DataJoint for MATLAB
- DataJoint Documentation
- DataJoint Tutorials
- Docker image for MySQL server configured for use with DataJoint
- Pharus — a REST API for interacting with DataJoint databases
- DataJoint Labbook — a front-end web interface for viewing and entering data