Data analysis methods in Astronomy and the Geo-Sciences are often surprisingly similar: they deal with information sources that include both vector and raster streams and operate in phases that include data integration, modeling and visualization.
As a specific example, similar "Big Data" methodologies are relevant for both Astro-informatics, Geographic Information Systems and Remote Sensing [References?].
We intend this repository as a collection of extensively documented yet executable notebooks providing parallel examples of data analytics in separate domains centering on astronomy and the geo-sciences.
Our objective is helping the astronomical and the geoscience communities interchange ideas and methodologies to identify and exploit the possibilities for collaboration and cross-pollination.
GitHub now supports Jupyter notebooks. To contribute to the repository, please feel free to fork it and let us know.
BIG SKY EARTH is an EU COST project.
The below chapters are rendered via the nbviewer in github, and is read-only and rendered in real-time.
Interactive notebooks + examples can be downloaded by cloning!