RDS schools are a great experience. It's probably not so easy to realize how useful they are just by thinking about programming and data management, so let's think about a musician who's given two weeks to go around a workshop full of instruments all along with other musicians like himself and some masters to teach how to use their instrument of expertise.
The course kicks off with what we could call "a few basic instruments", let's say (for our musician fellow) classical guitar, drum sets, bass guitar... Though quickly it gets more interesting with instruments he never heard of, some he might have heard about but thought of as too complicated and probably not even worth the try.
The RDS school is like having all of them made available, understandable and ready to use. Like this, now this musician will go compose, yet never as he did before; he will last less time on the basics and spend more time adding up in the complexity, worrying about the details and beautifying his creations. Data wise this is tremendously powerful; to gain the knowledge and the confidence to work in a dataset as if it were a simple melody and turn it into a masterpiece.
That's not the end of it. Ethics apply, taking part in the RDM schools is learning how to perform a good and FAIR data management and how to implement it into your own research. This is one of those things no one teaches, one of the RDS school’s best qualities and one of the things you take with you as part of your own set of values.
Furthermore you get to share with other scientists. People dealing with different data and scientific questions, people with a whole different perspective or even perhaps a not so different one but always with something to learn from. Out of this sharing experience it is easy to realize how the students were never a random set of individuals being picked to participate in a workshop but how they were always part of the same group, we were always a community, only now we know and are held accountable for our contribution to build upon it.
Anyone involved with the RDS schools can think of themselves as lucky but also as responsible to use and share the knowledge they gained and the tools they were shown to advance science, research, public data and policies and whatever else they are related with. They should also feel part of the open science movement and make sure that their input reroutes the ways scientific research has been taken by during the last decades.
After the course nothing is the same in your research. You start optimizing, get rid of useless programs or features that just complicate stuff, you forget the frustration of repetitive tasks that drain your time and energy (e.g. changing the name of a set of files one by one) and mostly you get time to do what you need, worry about the science, the ideas, the questions and flow through the data.
Also keeping a good management of the whole project so that it's reproducible, yet not only for others but for yourself! Have you ever wonder what you did in an analysis? perhaps something like: Why did I create that subset? That annoying sudden loss of memory. It doesn't happen to me... at least not anymore and I can really say that the RDS school had a lot to do with it.
So maybe all of this sounds like magic. I know... Yet, it's true! Although I must admit it doesn't comes that easy. After the workshop it takes some more time, a lot of practice and frustration, but it definitely pays off, not only you get to do what you need a lot faster and efficiently but also learn and become a better data scientist day by day.
So, you'll may be understand when I say that the way I see the RDS school is like going to an ice cream store on a sampling day and trying a little bit of everything. Afterwards you can decide what you want and how much of it you're going to need. On a long term... and especially on those days when everything I write seems to be working, the RDS school is definitely the tastiest ice cream store I've ever been to.
Jose López R - #dataSaoPaulo17 Alumni, #dataSaoPaulo18 helper.