11-17, 09:00–12:00 (Pacific/Auckland), WF503
This hands-on workshop walks through a full DGGS data pipeline. You'll use the FOSS tool DGGRID to index geospatial data and then publish it using pydggsapi, a new open-source server for the OGC API DGGS standard. Leave with a running web service on your laptop.
Discrete Global Grid Systems (DGGS) are getting more attention, and with the new OGC API - DGGS standard released, it's a good time for the open-source community to get practical, hands-on experience. This workshop bridges the gap between the theory of DGGS and a working implementation.
We'll show you why DGGS are so useful for integrating and indexing different data sources and spatial data analysis without the usual headache of map projections. Then, we work through a complete, real-world data pipeline using FOSS tools.
In this workshop, you will:
- take a standard geospatial file (like a GeoTIFF or GeoPackage).
- use the command-line tool DGGRID (https://github.com/sahrk/DGGRID | https://dggrid.readthedocs.io/latest/ ), generate grids and index this data onto a hexagonal grid
- we will introduce hierarchical indexing for ISEA3H and ISEA7H with the new Z3 and Z7 indexing systems in DGGRID
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in the decond part, we set up and configure pydggsapi (https://github.com/LandscapeGeoinformatics/pydggsapi/ | https://pydggsapi.readthedocs.io/en/latest/), an open-source Python server that implements the newly (to be) released OGC API - DGGS standard.
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we then point pydggsapi at the data you just created and launch the service
- we explore several ways how to interact with your new web service using a browser, or curl/Python notebook, and maybe even QGIS, to make queries and retrieve data.
Who should attend?
This workshop is for developers, data managers, and generally DGGS and geospatial enthusiasts who want to learn how to publish their data using this new paradigm.
Prerequisites:
Participants should be comfortable with the command line and have a basic understanding of what geospatial raster and vector data are. We can use Docker or plain Miniconda/Micromamba/Pixi Python environments to ensure the dependencies are easy to set up for everyone. Bring your laptop (Win, Mac, Linux, *BSD might all work).
By the end, you will understand the concepts of DGGS-indexed data and will have built a functioning DGGS-based web service yourself.
Alex is an Associate Professor in Geoinformatics and a Distributed Spatial Systems Researcher with many years of experience in open-source geospatial data management and web- and cloud-based geoprocessing with a particular focus on land use, soils, hydrology, hydrogeology and water quality data. His interests include Discrete Global Grid Systems (DGGS), OGC standards and web-services for environmental and geo-scientific data sharing, modelling workflows and interactive geo-scientific visualisation.
Alex completed a Marie Skłodowska-Curie Individual Fellow (MSCA) with our Landscape Geoinformatics working group on improving standardised data preparation, parameterization and parallelisation for hydrological and water quality modelling across scales and has now started a 5-year project on spatial modelling of soil properties using machine-learning.