Domain specific/interesting end goal use cases

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While initial development work will focus more heavily on synthetic data/toy examples of some relatively low-level artists, it is a good idea to keep in mind a wide range of applications, as that is the actual end goal that makes this work actually useful.

In particular the following, in no particular order:

- Oceanography/Geospatial data
- large datasets, subsampling data
- transforms into map coordinates
- integrations with cartopy, etc.
- Astronomy data
- It is a NASA funded grant, after all
- large datasets
- stress test units
- spatial-type data
- integration with data sources used in that domain
- Biological data
- Of particular interest to CZI grant
- Microscopy data/images
- Spectroscopy data
- It is my own area of expertise, I have several kinds of plots that serve a variety of levels of difficulty
- Specialized domain-specific data format
- Composing multiple artists
- particularly hard units support (spectroscopists can never agree what units to use, and like to say that length and energy units are interoperable)
- easy "quick" plots from a self describing data format
- multidimensional data, slicing into, etc.
- interactivity, stress testing the level of hooks provided to modify the plot
- Sports analytics data
- relatively unique visualizations
- see https://hockeyviz.com for many examples of a wide variety of plot types (made with matplotlib)
- potential interest for live updating

These are just a few of the domains for which this dataset-centric approach may be useful, feel free to add more.

Das Issue nennt keine Dateien, Tests oder Einstiegspunkte; beginne damit, den aktuellen Umfang des Projekts anhand der aufgeführten Anwendungsfälle aus Ozeanografie, Astronomie, Biologie, Spektroskopie und Sportanalyse zu überprüfen. Als erledigt gilt die Arbeit, wenn ausgewählte Anwendungsfälle in konkrete, priorisierte Anforderungen oder nachgelagerte Implementierungs-Issues überführt wurden.

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