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• U19 – brief description overall project goals, competing circuit theories being developed/studied/integrated: Build a multiscale biofidelic simulation of a zebrafish, leveraging nano-, micro-, and meso-scale anatomy and physiology, as well as detailed behavioral data

• Description of how Data Science Core is complying to the criteria of the FAIR principles:

1. Findability: Data and metadata will be deposited in public repositories - ZBrain 2.0, Brain Image Library (BIL), Brain Observatory Storage Service & Database (BossDB), and another repository currently in development. Metadata will be downloadable as JSON files and stored in a Laboratory Information Management System (LIMS). Code will be deposited in Github or DockerHub, with version control. Data and code will link to each other where relevant.
2. Accessibility: All data and code will be open-source (see #1 above). No login or registration will be required to access either code or data resources.
3. Interoperability: Data and code will link to each other, with well-described experiments and analyses so users can leverage both. We will use common vocabularies (e.g., JSON files).
4. Reusability: All data and code will be in commonly used formats, thoroughly described, and relevant papers will be linked. All data sets will be released under the Open Data Commons Attribution (ODC-By) license. All software and course material will be released under the Apache 2.0 license. Both of these licenses are permissive, and will permit free usage.

• List of Data Types in U19:

1. Behavior
   1. Raw videos using standard compression algorithms and associated header files containing all behavioral metadata
   2. Processed data including pose data (e.g., location of zebrafish pectoral fins, tail, body, angles of eyes, and heading, on each frame)
2. Imaging techniques
   1. High-resolution confocal volumes
   2. Electron microscopy (EM) zebrafish images
   3. 2-photon calcium imaging videos and processed data (e.g., segmented cells and corresponding fluorescence traces)
   4. Light sheet calcium imaging videos and processed data (e.g., segmented cells and corresponding fluorescence traces)
3. Software
   1. Code deposited in Github
   2. Dockerfiles deposited in DockerHub
   3. Amazon Machine Images

• Common Data Elements in U19:

Many groups are generating behavioral data (acquired as raw videos) and functional calcium imaging data (acquired with 2-photon or light sheet). All groups are developing software.

• Data Sharing goals in U19:

1. Deposit all imaging data in public repositories. Confocal data will go to ZBrain 2.0 and BIL, while EM data will go to BossDB.
2. Deposit behavioral data - raw and processed - in a to-be-developed repository in the cloud backed by Amazon Web Services (AWS).
3. Our goal is to enable collaboration between all the labs of the U19 by freely sharing data, and to make this all available to the community no later than time of publication.

• Data science tools being used in project:

1. ZBrain 2.0
2. Brain Image Library
3. Brain Observatory Storage Service & Database
4. Github
5. DockerHub
6. Amazon Machine Images
7. Scikit-image
8. Neuroglancer
9. CloudVolume
10. Terastitcher
11. N4-ITK
12. Voluseg
13. CaImAn
14. Suite2p

• Data science tools being developed for project:

1. ZBrain 2.0
2. Brain Image Library
3. Brain Observatory Storage Service & Database
4. Github
5. DockerHub
6. Amazon Machine Images
7. Scikit-image
8. Neuroglancer
9. CloudVolume
10. Terastitcher
11. N4-ITK
12. A repository for sharing of zebrafish behavioral data
13. Neuroscience as a Service

• Data science approaches to be shared with other U19’s:

1. Scikit-image
2. Neuroglancer
3. CloudVolume
4. Terastitcher
5. N4-ITK

• Data science challenges that could benefit from discussion with other U19’s:

1. Collaborative brain atlasing
2. Sharing analysis and modeling pipelines

Link to Data/Model Reuse abstract, [Link] 

2021 Brain PI Meeting

Update:

Link to Poster:

Demo:

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