Enhance IOOS colocate library for web-based query, preview and download of oceanographic data in ERDDAP

[mwengren]

Project Description:

The ioos/colocate project started in OceanHackWeek 2019 as a way to find similar (colocated in space, time) oceanographic data hosted in ERDDAPs worldwide - see Awesome ERDDAP's server list for an idea of ERDDAP's popularity. The initial version was intended to be run as a lightweight UI in a Juypter Notebook environment, but it doesn't need to be limited to be notebook-based only. A number of enhancements can be made from the existing code base to extend colocate's capabilities:

• improve query functionality and performance of colocate's ERDDAP query implementation, including update the erddapy API dependency and/or implement better parallelism in query algorithms
• develop a standalone/webapp-like version to run via Panel or PyScript
• allow interactive preview and/or download of ERDDAP datasets returned via user query (e.g. generate a timeseries plot for CF timeSeries or timeSeriesProfile datasets, scatter or profile plot for trajectory datasets)
• build a colocate extension for Jupyter Lab

See the following issue in ioos/colocate for more info about the project and to get started: ioos/colocate#29.

Expected Outcomes:

The colocate package is a useful tool for lightweight discovery of in situ oceanographic data. IOOS sees benefit in developing tools to assist users in searching, previewing, and downloading oceanographic data from the constellation of ERDDAP servers operated worldwide. Any or all of the enhancements above will help to bring IOOS' and other organizations' oceanographic data to the fingertips (and data analysis environments) of scientists, data analysts, and general users worldwide.

Skills required:

Python, erddapy/ERDDAP, Panel/HoloViz/DataShader, PyScipt, Jupyter Notebook, Jupyter Lab, familiarity with netCDF and oceanographic data standards including Climate and Forecast (CF) conventions is helpful but not required - willingness to learn the data types is ok

Mentor(s):

Micah Wengren (@mwengren), Mathew Biddle (@MathewBiddle), Filipe Fernandes (@ocefpaf)

Expected Project Size (175 or 350 hours):

175 or 350 hours

Difficulty:

Medium/Hard

[mwengren]

Closing to clean up for GSoC 2024 application