This is an anti-pattern. Do not make DSLs for subdomains of science. All scientific data can be stored and queried using general-purpose data analysis tools.
because sql and other well-established systems already do this and tools like this can be built on those systems without creating yet another domain-specific tool.
I’m curious how this compares to traditional tools (like scripting in Python/R) for analyzing such datasets, both in ease of use and performance. Also, could similar query languages be developed for other fields (genomics, imaging, etc.) to empower domain experts? It’s cool to see a new DSL in academia
This is an anti-pattern. Do not make DSLs for subdomains of science. All scientific data can be stored and queried using general-purpose data analysis tools.
Why not if it is to facilitate new discoveries and to extend the reach of computational tools to large swaths of clever and productive people?
because sql and other well-established systems already do this and tools like this can be built on those systems without creating yet another domain-specific tool.
I’m curious how this compares to traditional tools (like scripting in Python/R) for analyzing such datasets, both in ease of use and performance. Also, could similar query languages be developed for other fields (genomics, imaging, etc.) to empower domain experts? It’s cool to see a new DSL in academia