Datacubes form an acknowledged cornerstone for analysis-ready data – the multi-dimensional paradigm is natural for humans and easier to handle than zillions of scenes, for both humans and programs. Today, datacubes are common in many places – powerful management and analytics tools exist, with both datacube servers and clients ranging from simple mapping over virtual globes and Web GIS to high-end analytics through python and R. This ecosystem is backed by established standards in OGC, ISO, and further bodies.

In this short course we introduce the concepts of datacubes, discuss different service API standards, and explore hands-on together how to access, extract, analyze, and reformat data from datacubes. Particular emphasis is on timeseries wrangling. The examples can be recapitulated and modified by participants with online access. Further, building up datacubes from a variety file sets is discussed. Ample room will be left for discussion, inviting participants to table their datacube-related problems.

After this course, participants
- Know the core datacube concepts, terminology, and standards
- Understand the advantage of the harmonization done in datacubes and its contribution to analysis-ready data
- Know sample datacube services and can work with them, with some self-chosen client
- Understand how datacubes can be built from file sets