• Implement a Project edit button, file and project rename functionality, fix edit project popup , allow editing list of notebooks , and add images to each type of notebook. • Implement support for Jupyter notebooks. Users should be able to upload, view, and edit Jupyter notebooks on the platform. Use Jupyter Lite, or nbviewer, or nbconvert to render notebooks in HTML format. • Allow users to fork existing projects. Forking should create a new project that is linked to the original, allowing users to experiment with changes without affecting the original project. • Improve the project creation and editing process. Add validations for project names to ensure uniqueness. Enhance the project edit functionality to prefill forms with existing information and update project names and routes when edited. • Implement a user permission system to differentiate between project members and followers. Users can join projects as members or follow them with the project owner's permission. • Set up a continuous integration system for automated Docker container generation. • Migrate the project's blob storage to Jetstream. Ensure a seamless transition with minimal downtime and data loss. Set up automated, regular database backups. • Bug Fixes: Address existing bugs in the platform, such as issues with the registration code, disappearing navbar account menu, and join button behavior, to improve user experience and platform stability. • Implement an organization system where users can create and manage organizations. Organizations can have multiple projects and users associated with them. Define roles such as admin, members, and followers within organizations to manage permissions and access levels. • Implement comments in projects and logs along with a reply-to field, vote field to up/down voting, and a ‘flag’ field for flagging.

The proposal focuses on prospective ideas that can be employed for enhancement of the existing INCF Impact Visualization Portal. It goes into depth, explaining every idea's importance and possible way of implementation. Additionally, it proposes novel ideas, as well as ideas for upgrading the existing features.

The project is about incorporating new features into an existing 3D viewer which allows for visualisation of cells and networks using the NeuroML standard. Right now the viewer is limited to only viewing the model, whether it is a single cell or a complete network, but at the end of the project it should be a fully equipped 3D viewer with GUI to interface with the user. The user should be able to get as many information as he can about the model using an intuitive GUI with a short learning curve, using “on click” or “on selection” methods to provide according information and providing easy access to views of cells showing ion channel distributions, segment groups, etc. A critical aspect of the project is to ensure high performance with the Vispy viewer to allow visualization of large scale networks. Being able to interact with a model, significantly boosts the understanding of its structure and dynamics. Furthermore, the additional information that will be added can make this viewer an invaluable tool both for an experienced scientist and a beginner in the field, as long as they have some knowledge of python, by providing the capability of exploring new models in a fast, efficient and intuitive manner. Additionally, the Vispy viewer should be embedded into NeuroMLLite-GUI. Options for using the Vispy viewer inside Jupyter notebooks/JupyterLab should also be investigated, as Jupyter notebooks are gaining popularity rapidly.

Neuroptimus, an open-source parameter optimization software tailored for neuroscience applications, has been instrumental in advancing the construction and optimization of biologically detailed models, utilizing algorithms such as evolutionary algorithms and swarm intelligence. Neuroptimus includes a graphical user interface (GUI), and works on multiple platforms including PCs and supercomputers. Building upon its success, this proposal aims to enhance the GUI of Neuroptimus to further streamline the parameter optimization process.The project targets to address key areas of improvement within both the graphical user interface and command-line interface of Neuroptimus. By integrating missing functionalities and refining existing features, the goal is to enhance user experience, flexibility, and accessibility. Specific enhancements include enabling users to save and load optimization settings seamlessly within the GUI, providing real-time monitoring of optimization progress, enhancing the interpretability of optimization results through various output formats, and facilitating analysis and visualization of both intermediate and final optimization outcomes. Through these enhancements, the Neuroptimus GUI will become more informative, user-friendly, and conducive to efficient parameter optimization for biophysical models in neuroscience research. Project Deliverables: 1- Implementing Saving and Loading Optimization Settings. 2- Implementing Progress Monitoring Functionality. 3- Implementing Saving Optimization Results in an Interpretable Format. 4- Extending UI with Visualization Options for Final and Intermediate Results. 5- Researching and Proposing Additional UI/UX Enhancements.