Hosted by the Harvard Medical School, the Data Workflows for Neuroscience Teams workshop brought together researchers and technical experts to explore best practices in scientific data management, pipeline design, and collaboration. The three-day event featured hands-on sessions, interactive discussions, and case studies—highlighting how tools like DataJoint Elements support scalable, reproducible neuroscience.
Day 1 – Collaborative Workflows & NIH Requirements
The workshop opened with sessions on designing collaborative neuroscience workflows and navigating NIH data management requirements. Dimitri Yatsenko led discussions on integrating code and data management strategies, followed by a hands-on coding session to build data pipelines from scratch.
Day 2 – Multimodal Data Integration & Cloud Architecture
Milagros Marín led a practical coding workshop on combining multiple data modalities using DataJoint Elements. Discussions with Dimitri Yatsenko, Thinh Nguyen, and Marín covered advanced topics including software architecture, technical infrastructure, and leveraging cloud computing for neuroscience workflows.
Day 3 – Case Study: The Sabatini Lab Pipeline
The final day focused on real-world application. Dr. Janet Wallace, Sr. Scientist in the Sabatini Lab, walked participants through the lab’s extensive data pipeline, exploring and visualizing data with Thinh Nguyen. Attendees had opportunities to engage in informal discussions and network with fellow researchers and developers.
This workshop underscored the growing need for robust, transparent, and collaborative data practices in neuroscience—and demonstrated how teams can meet that challenge with modern tools and workflows.
Thank you to all the organizers, speakers, and participants who made the event a success.
