Declarative Dashboards for Volumetric Data

Project Description

This project will explore developing a custom front-end for volumetric (i.e., astrophysical, oceanographic, weather, finite element) data accessible to Whole Tale. This will include developing a dashboard of analysis methods on these datasets, and utilizing existing open source libraries for exposing methods to individuals. The final result will be both a dashboard and a downloadable set of machine-readable representations of the current state of the dashboard, which can be re-ingested as a secondary tale.

Necessary Prerequisites:

Experience with scientific datasets
Experience with Jupyter, or alternately, web technologies for visualization such as vega, D3, leaflet, etc.
Experience with version control systems such as git

Desirable Skills / Qualifications:

Experience with python-based tools for data analysis, such as numpy, yt, dask, and xarray.
Experience with Jupyter dashboards (such as voila) and declarative user interface systems (such as SwiftUI, ipywidgets, etc)
Domain knowledge in one or more areas of the natural sciences such as astronomy, weather, oceanography, seismology, etc.

Expected Outcomes:

General deliverables:
- presentation
- weekly meetings
- blog post
- git repository
Specific deliverables
- template tale
- dashboard specification

Primary Mentor: Matt Turk

Secondary Mentor: Kacper Kowalik