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Reproducibility is one of the corner stones of science: when studies cannot be reproduced it is hard to convey that they contain new findings of general truth. We constrain ourselves here to computational aspects of spatial data science, and discuss the challenges posed by always evolving software, scientific software developer communities, upstream and downstream dependencies, the publishing industry, and report on experiences from developer communities, and look at convergence in the spatial data science software ecosystems.
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