If you would like to contribute to any of these features, we ask that you read our contributing guidelines and let us know through the appropriate channels indicated there.
Improvements to the IaC platform that forms the backbone of the NeuroCAAS Project. Most of these improvements will be implemented as changes to this repo. Many of these changes are prerequisites to changes in other sections (see dates).
- Create “hub” users and “member” users: hub user is vetted by us, and assigned a budget- they can share with member users in their group. Reduces vetting burden on us. (Q3 2020)
- Create an option to delete data on successful job completion, set as default.
- Tag compute resources when jobs are launched for higher fidelity monitoring and improved security. (Q3 2020)
- Load test website with Locust. (Q3 2020)
- Move from SSM RunCommand Document based workflow to SSM Automation Document workflow for higher fidelity status updates on job progress/success, cleaner handling of termination. (Q4 2020)
- Move from single Lambda function based execution of jobs to AWS Step Functions. Distributes workload, reduces time that a single lambda function is active, and allows for easy analysis chaining. (Q4 2020)
- Add long term glacier storage in S3 for datasets. Facilitates analysis reproducibility workflows (see next). (Q4 2020)
- Provide DOIs for analysis blueprints+configs+data so they can be referenced, recreated, and cited (Q1 2021)
- Instead of referencing custom built AWS AMIs in blueprints, move to referencing Docker Containers as a more general and easily updated solution. (Q1 2021)
- Move users from IAM to Federated users expand potential user base size. (Q1 2021)
- Add streaming data capability for real time capable analyses by integrating real time workflows with Amazon Kinesis. (Q3 2021)
Independent software package for developers who would like to contribute their neuroscience data analyses to NeuroCAAS.
- V1: Streamline installation: remove python contribution api from main repo, package independently. Removes need to download full NeuroCAAS IaC repository. Also streamline job testing: remove need for developers to manually upload data and write submit files themselves. (Q3 2020)
- V2: Handle Docker integration: given a docker image, load that image onto a provided ami. (Q1 2021)
- V3: Incorporate GUI tools in developer package for per-analysis GUI customization. (Q2 2021)
Internally managed/developed contributions to NeuroCAAS Platform. Goal: Improve the developer package by adding these analyses using successive versions.
- Add YASS/other spike sorters (Q3 - Q4 2020)
- Update DLC to latest version/other pose trackers (Q4 2020)
- Add pipelines for genetics (Q3 2020)
- Add pipelines for generative modeling (Q4 2020)
- Add pipelines for cell segmentation, add GUI for pose trackers requiring manual labels through developer package V3. (Q2 2021)
Development of the primary interface for this project. Follows many of the backend improvements specified in first section. Will be hosted through subsidary repo jjhbriggs/neurocaas_frontend.
- Eliminate configuration parameter errors before jobs begin with website based linting (Q3 2020).
- Add support for “hub” and “member” users [see backend improvements] (Q4 2020)
- Introduce workflow for citable analysis workflows with long term glacier storage + DOI provided IaC blueprint (Q1 2021)
- Make analysis progress more easily visible across multiple jobs with GUI (Q1 2021)
- Add demo videos/code for currently hosted analysis algorithms. (Videos: Q3 2020, Code: Q4 2021)
Independent software package for users who would like to use NeuroCAAS in code. Useful for workflows difficult to integrate with web frontend.
- Brainstorming/prototyping: Find way to easily list all available analyses in package (like passing string to boto3 client?) (Q3 2020)
- Integration with Datajoint Elements for modularity of our analyses with different preprocessing/postprocessing while maintaining data integrity.
- V1: create a package that uploads files to s3, and then downloads them back from s3 once job is completed. (Q3 2021)
- V2: provide option for real time streaming data analysis from generic camera sources (Q4 2021)