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Bachelor Thesis of student assistants Tom and Nick

Two of the o2r student assistants have just finished successful their bachelor theses. Congratulations! 🎉

This blog post introduces the excellent work by

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New papers out about 'Practical Reproducibility in Geo' and the 'Rockerverse'

Two papers have been published this week by o2r team members Daniel and Edzer. They shed a light on the practical aspects of publishing computational geospatial research in a reproducible way and the enourmous number of projects and opportunities of using containers with R to achieve reproducibility. Please share widely!

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Beyond o2r: collaborations and community activity for more open and reproducible science

The o2r project has its primary goals in providing tools to enhance scholarly communication. We build technology to help solving relevant problems. With the Executable Research Compendium and supporting software, we provide a different, more holistic take on how research output should look like in the future, especially if data and software are involved in the scientific workflow. However, tech is not all we do and o2r team members actively work with the GIScience community and the broader scientific community. This blog post briefly introduces two recent collaborations that are less about technology and more about community, culture, and people.

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o2r student assistant about impressions of reproducibility ready to start a career in research

“Geoscientist with experience in or willingness to learn R programming for reproducible research wanted!”

I had just completed a beginner course in R programming for my master’s thesis and saw my chance to further develop this knowledge and enter the field of geoinformatics, even get a little away from the pure ecology of my master studies in landscape ecology. I had never before heard of the words “reproducible research”, neither heard of any reason why this topic is of importance. So I took the job and worked my way in. After a couple of months

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Introducing geoextent

geoextent is an easy to use library for extracting the geospatial extent from data files with multiple data formats.

Take a look at the source code on GitHub, the library on PyPI and the documentation website. You can view and test geoextent implementation through interactive notebooks on with a click on the following binder.


Here is a small example how to use geoextent.

geoextent -b -t -input= 'cities_NL.csv'

The output will show the rectangular bounding box, time interval and crs extracted from file data, as follow:

{'format': 'text/csv',
 'crs': '4326',
 'tbox': ['30.09.2018', '30.09.2018'],
 'bbox': [4.3175, 51.434444, 6.574722, 53.217222]}

The input file used above was obtained from Zenodo. The map below

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