Comments (4)
I would favour "awesome" datasets as being those that are easy to work with, or really are just too awesome to ignore.
from awesome-open-geoscience.
I think we can grow it organically. I'm not sure if there are enough awesome data to create the mold up front. It's supposed to be awesome after all
from awesome-open-geoscience.
Jesper has a good point about not creating a mold up front, maybe we encourage people to define what the dataset is "awesome" in the readme somewhere? It would be helpful to know why its a really cool dataset and not just what is in the dataset.
Perhaps under the section title we add "Please describe what is 'awesome' about each dataset not just what is in the dataset."
from awesome-open-geoscience.
Maybe it's even enough to give a little "awesome description" in the PR?
People coming to the list expect awesome content, so the content might be enough for them to click through, with us having vetted the awesome-ness threshold. (I'd like to keep the descriptions on the list as short as possible).
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Related Issues (20)
- Data Repositories HOT 2
- pyrocko link superseded HOT 3
- Geoscience softwares HOT 3
- Add package health badges HOT 4
- Travis CI keeps failing due to link issues that aren't easy to understand HOT 1
- rename default branch to `main` HOT 2
- Broken link https://www.npolar.no/quantarctica/ HOT 1
- Public data repositories HOT 1
- Proposal to get more maintainers HOT 4
- Broken link: http://fuzzylas.appspot.com/
- 3 Link Problems to fix HOT 1
- Need facies detection model for segy data HOT 1
- Geoscience
- Question: "Geophysics" vs. "Simulation and Modelling" HOT 1
- Add DOI badge HOT 3
- Fix the vtki/vista/pyvista link HOT 1
- What defines "awesome"? HOT 8
- anyone know of grainsize , rock counting, etc software?
- GeoStat-Framework HOT 4
- look at /awesome-coastal and evaluate
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