Colocate was started as a way to query the global landscape of ERDDAP servers and identify datasets that share common:
geographical position (lat/lon)
time coverage
data types (CF standard names)
The end goal was to make an actual app that could be run either on the web or locally/on-demand by a desktop user to find, visualize, and download data of interest to them. A number of improvements to the UI/UX of the app could be made that would allow users to:
more easily create/generate query parameters listed above
dyamically preview dataset results returned via queries (both map preview and timeseries, profile, or scatter plots as appropriate based on CF featureType for example)
select datasets to extract/dowload directly through the UI (see #25)
The end result could be a standalone app that runs via Panel or PyScript or some other browser-based or server-based dashboard framework.
Example graphic showing current map-based preview capability in HoloViz/DataShader:
More recent releases of HoloViews and other libraries may provide many of these capabilities out of the box and only need to be implemented. Other libraries as well have come along that have made the original vision of the app more achievable.
Expected Outcomes:
An improved colocate standalone app that that better displays ERDDAP dataset results, allows for dynamic/interactive preview of datasets, and direct download from the app for ERDDAP datasets that are not prohibitively large
Project Description:
Colocate was started as a way to query the global landscape of ERDDAP servers and identify datasets that share common:
The end goal was to make an actual app that could be run either on the web or locally/on-demand by a desktop user to find, visualize, and download data of interest to them. A number of improvements to the UI/UX of the app could be made that would allow users to:
The end result could be a standalone app that runs via Panel or PyScript or some other browser-based or server-based dashboard framework.
Example graphic showing current map-based preview capability in HoloViz/DataShader:
More recent releases of HoloViews and other libraries may provide many of these capabilities out of the box and only need to be implemented. Other libraries as well have come along that have made the original vision of the app more achievable.
Expected Outcomes: An improved colocate standalone app that that better displays ERDDAP dataset results, allows for dynamic/interactive preview of datasets, and direct download from the app for ERDDAP datasets that are not prohibitively large
Skills required: Python: HoloViz, DataShader, Panel API, PyScript, plotting libraries (TBD)
Project Size 175 or 350 hours
Difficulty: Medium