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I post this in response to the lack of a Julia tag for articles like this:

Julia has been proposed before, but I think the audience of this site for that sort of thing is pretty small. Except for the ai tag, there isn’t much on this site here relevant to the data scientist in general as ai is too-specific, and Julia is still pretty small compared to the visibility of major projects, but of some interest to the plt and lisp people here due to its relatively unique language features.

I don’t think the differences between the languages and tools are significant enough to have separate tags for julia, scipy, R, matlab, and stata as of this point, and there is a great deal of overlap between users of Julia and Numerical/Scientific Python.

In summary, julia seems to be too small of a community here to justify a specific tag just yet, but computational science is well-defined enough to warrant it. ai exists, but is a subset of data science. Computational science also includes modeling and simulation tools which might not fit under AI/Statistics, and is too far removed from compsci.

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    I like this proposal, especially because it covers modeling and simulation–things that would otherwise maaaaybe fit into graphics but not always.

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      I like this idea, there seems to be a lack of a more data-science related tag.

      I submitted https://lobste.rs/s/u4m0lr/managing_messes_computational a few days ago, and it would also benefit from the scicomp tag. I ended up putting python and practices, but none is a good descriptor of the content.

      But it is somewhat confusing to have scicomp and compsci as tags, since they are quite similar…

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        I’m open to alternatives. Maybe datascience or datasci, but I feel that it might limit it too much to AI and statistics, which could be grouped under ai, and that would leave out the computational modeling. Also, science is a tag used often for scientific computing as of now, but it’s more generally understood as scientific results and discovery, and there are many things of interest to the domain of scientific computing that are of little interest to practicing scientists, such as what goes on under the hood.

        I guess data engineering would be left out if we don’t go with datascience, but perhaps a data or bigdata tag could better suit them.

        As of right now, I am sticking with scicomp because human language is not commutative, and that we have the opportunity to create a niche for discussion in a growing field that could also benefit lobste.rs as a whole.

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          I’ve been thinking of submitting a datascience tag proposal for a while now. I think the two are distinct enough that we’re better off with both.

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            I think data is good. bigdata and scicomp can both be considered sub-fields of a wider data field, and there is crossover between them. Individually those tags are quite specific, maybe even niche?