Challenge 33 - Data Stores plug-in for GIS #11
Description
Challenge 33 - Data Stores plug-in for GIS
Stream 3 - Software Development for Earth Sciences Applications
Goal
The overall goal of the challenge is to create a proof-of-concept for a plug-in which facilitates the integration of DSS (Data Stores Service) Data into a GIS platform.
Mentors
Angel Lopez Alos, Petrut Cobarzan, Gionata Biavati (all ECMWF)
Skills Required
- Python
- QGIS (or any GIS platform)
- OGC Services (WMS, WMTS,..)
- Data formats (NetCDF, Grib)
Description
There are multiple dedicated tools viewers that allow the visualization of DSS Datasets. However, there is no easy way for GIS users to easily integrate this data on their platforms as Layers that can be combined with others. The aim is this challenge is to explore and implement a proof-of-concept of a plugin for a GIS platform that allows to discover, subset and render a data layer powered by the DSS.
Examples of DSS Data Visualization can be found on thematic applications or in the WEkEO Viewer.
There are different approaches, end-points and tools that can be used for the challenge depending on the functional capabilities to be implemented:
- CDS API Package
- Catalogue API. This exposes all the information about the DSS Catalogue (resources, forms definition, constraints).
- Retrieve API. This allows to submit and retrieve Data.
- ARCO Data Lake - STAC Metadata
- WMTS Service: restricted to certain layers update on the ARCO Data Lake (Zarr Format). These are those visible in WEkEO. See example.
- Earthkit: Set of expert tools that allow to access, manipulate and visualize data.
Similar Plug-ins available for other Copernicus Data can be explored for inspiration:
- https://marine.copernicus.eu/services/user-learning-services/qgis-plugin-cmems-netcdf
- https://dataspace.copernicus.eu/news/2023-9-4-qgis-meets-copernicus-data-space-ecosystem-new-plugin
Evaluation Criteria
- Feasibility
- Transferability
- Easy to maintain / Future-proof approach
- Matching requirements