I think that the key is to take an informative approach rather than a forceful one. If people are happy using whatever they're currently using, don't try to force them to change. There are, however, usually people who are in a great deal of pain trying to solve the problems they're tackling with the tools they have – those people are often extremely relieved to find something that can make their lives easier. People are themselves in the best position to know this, so if you show them something like Julia and what it can do, they'll know if they have a use for it or not. That said, showing examples that connect with them and allow them to imagine how to apply it in their work is key.
On Mon, Jul 25, 2016 at 7:18 AM, Tamas Papp <tkp...@gmail.com> wrote: > Hate to sound like a curmudgeon, but language evangelism frequently > backfires, and if it is coming from a person not working in a particular > problem domain, the best you can expect is a shrug. Which is fair I > guess, "I don't know what you are doing but I am sure you would find > language X a good match for it" doesn't sound too convincing. > > On the bright side, Julia is spreading fast in many communites, so if it > is useful for those scientists, I am sure they will find it on their own > quickly. When they are ready; and when the language is ready. > > On Mon, Jul 25 2016, Chris Rackauckas wrote: > > > It seems like most of what they do is biostatistics/bioinformatics. I > would > > show them PyCall and RCall. Knowing that you easily have all of those > > libraries (and your previous libraries) is great. Also show them the > > JuliaStats stuff. > > > > In fact, ask them what they'd want to add to Julia if they had the time. > > You'll run the gambit and show them a package which already does it. This > > happens all the time on the Gitter: someone new comes saying "hey I want > to > > learn Julia. It's new so it doesn't have many packages... does it have > > something for this? Oh it does... this? Oh it does... this? Oh..., its > > package system is actually pretty complete." This combined with the > > R/Python/MATLAB glue really makes one confident that Julia at least has > > enough to try on a real project (and get hooked). > > > > I'd also show them Plots.jl. It is also much nicer than other plotting > > libraries I've used before. The fact that you can switch backends with > the > > same code means that you get all the new updates "for free" when backends > > come out (I'm looking at GLVisualize!) > > > > Definitely show them the BioJulia group. > > > > Show them @parallel and pmap. If they have HPCs, show them how to just > give > > Julia the machinefile and together you already have multinode parallelism > > for embarassingly parallel problems. > > > > Last but not least, show them the community: julia-users, the Gitter > > channels for chatting with the devs, etc. Knowing that there's always > help > > right there is really wonderful. > > > > On Monday, July 25, 2016 at 2:44:16 AM UTC-7, Job van der Zwan wrote: > >> > >> *TLDR: I'd like to show Julia to my colleagues, but don't have a clue > >> which cool packages and features I should show off to them, because I > don't > >> do any scientific work myself.* > >> > >> Hi, > >> > >> I'm an interaction designer working for a research group at Karolinska > >> Institute[0]. Basically, I'm a glorified front-end webdev. I don't do > any > >> scientific work myself, I'm just building a web-based interface for > >> browsing and visualizing single-cell data for them. So my use-cases > don't > >> seem to align with Julia's strengths, but I like the design of the > >> language, the ideas behind the project and have been following its > >> development great pleasure. > >> > >> Last week while watching a bunch of JuliaCon videos during a lunch > break, > >> one of my colleagues asked what the video was about. I tried to explain > the > >> Julia project to him, as well as the language's strengths and > weaknesses. > >> Sadly, I didn't really do a good job of it, since I don't actually > program > >> in it myself. He said it looked a lot like Matlab (his language of > choice) > >> and was interested in the free-and-open-source aspect. But he expected > >> there to not be enough packages yet for him to work with it and was > >> sceptical about whether switching to it would be worth it. I tried to > >> explain that Julia can call out to Matlab code with practically no > >> overhead, but he didn't really look convinced (and I didn't have a > working > >> Julia environment to show it off to him either). While Jupyter was also > a > >> turn-off, since he doesn't like notebooks, but the Juno video > compensated > >> for that a lot. > >> > >> Basically, I'd like to show Julia to my colleagues, give them some > >> pointers on where it might be fun to start playing with it, what are > some > >> of its amazing features *that matter to them*, but I don't have a clue > of > >> what I should focus on to do so. > >> > >> The researchers I work for are molecular neurobiologists. They're doing > >> pretty well, having published in Science last year and this year, see > >> here[1] for a list of publicatiosn. Currently Anaconda is the "lingua > >> franca" platform, but some in the group prefer Matlab or R over Python. > Of > >> course, one of Julia's selling points is that it's a very "inclusive" > >> language, so I definitely could show that, but I don't know what else to > >> demonstrate. I'm hoping there are researchers here with similar enough > >> use-cases for Julia who could give me some suggestions about what kind > of > >> things they might really like over their existing solutions. > >> > >> Cheers, > >> Job > >> > >> [0] http://linnarssonlab.org/ > >> [1] http://linnarssonlab.org/publications/ > >> > >
