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 aims to be a data sharing and hosting resource for crowdsourced-analysis of 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 of 2023.
Project is still in progress and a demo site is available at: https://analysim.tech
Source code: GitHub - soft-eng-practicum/AnalySim
Main Technologies: Angular (Typescript), HTML/CSS/Bootstrap, ASP.Net Core (C#), PostgreSQL
Technologies for analysis notebooks: JavaScript (ObservableHQ, D3.js, Vega, Plotly) and Python (Jupyter)
Skill level: intermediate/advanced preferable
Time commitment: Half-time (175 h)
Lead mentor: Anca Doloc-Mihu (adolocm@gmail.com)
Project website: https://analysim.tech
Backup mentors: Cengiz Gunay (cengique@gmail.com)
Mentor break: Planned break for both mentors due to CNS meeting: June 28 - July 24 still available, but with limited email contact.