Mentors: Cengiz Gunay <cgunay@ggc.edu>, Anca Doloc-Mihu, <adolocm@gmail.com> (Planned break for both mentors due to CNS meeting: July 5 - July 9 with limited email contact)
Skill level: intermediate/advanced preferable
Required skills: C#, .Net, HTML/CSS/Bootstrap, Angular, TypeScript, PostgreSQL, Docker
Time commitment: Full-time (350 hours)
About: AnalySim is a data sharing and analysis platform that seeks to simplify the visualization of datasets. With Analysim, researchers can collaborate by hosting their data and publishing their analysis notebooks to the world, or browse through multiple user-generated projects. Analysim is currently being hosted on the NSF-funded ACCESS-CI project infrastructure, but it can also be deployed independently via Docker.
AnalySim aims to be a general data sharing and hosting resource for crowdsourced-analysis, but it provides additional support for a specific type of dataset: one where many parameter combinations need to be tested and measurements are recorded for each instance. These datasets are very useful in mathematical modeling of natural phenomena, such as in computational neuroscience. We provide easy sharing, analysis, visualization, and collaboration capabilities on these datasets. In this GSoC iteration, we are improving on features developed in the summer and winter of 2024.
Aims: Helping run the controlled beta testing by fixing issues and adding new features for forking datasets/projects, following/joining projects. Improving usability of CSV data browser, versioning, and querying components.
Website: Project is still in progress and a demo site is available at: https://analysim.tech and a development version is at https://dev.analysim.tech
Source code: GitHub - soft-eng-practicum/AnalySim ยท GitHub
Tech Keywords: Angular (Typescript), HTML/CSS/Bootstrap, .Net Core (C#), PostgreSQL, and for analysis notebooks: JavaScript (ObservableHQ, D3.js, Vega, Plotly) and Python (Jupyter)