Session 6: Research workflows for collaborative neuroscience
Co-Chairs: Dimitri Yatsenko (DataJoint), David Feng (Allen Institute), Erik C. Johnson (JHU APL)
Speakers: Kabilar Gunalan (DataJoint), Milagros Marin-Alejo (DataJoint), Frank Zappulla (Code Ocean), and Daniel Xenes (JHU/APL)
Location: Presentation Room 2
To tackle the challenging questions of the brain, scientists are turning to innovative strategies to automate and organize their research. Automated research workflows integrate computing infrastructure, automation, instrument integration, advanced data operations, and machine learning to enable researchers to process vast amounts of data and analyze complex patterns. This enhances the speed, accuracy, and reliability of collaborative research activities and enables scientists to generate new insights and knowledge that were previously unattainable.
The implementation of automated research workflows is not just about technical solutions but also about creating novel team structures that foster collaboration and innovation. With these tools, researchers can work more efficiently, share knowledge more easily, and focus on the intellectual challenges of their research.
In this workshop, three teams will present approaches to workflow management, team organizations, software tools, and online platforms and resources for organizing studies. The presentation will comprise short lectures followed by hands-on tutorials.
The target audience are students, postdocs, and investigators in data-intensive neuroscience research.