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There seems to be constant conflict over data management in fields of scientific research. While rigorous data management can lead to improvements in the accuracy, reproducibility, and credibility of a scientist’s published results, it can also seem irrelevant and difficult to instate at the beginning of the research process. The research cycle is a dynamic process, and scientists often lack the time to adapt their data management systems to meet the needs of an evolving, experimental workflow.
This is a companion discussion topic for the original entry at https://blog.algebraicjulia.org/post/2020/11/sql-as-hypergraph/