A soft introduction to open science | R-Bloggers

Read it in: Français.

This summer I had a great time to Society for Canadian ornithologists meeting SaskatoonCanada. It was super exciting to meet SungRopsci champion and colleague ornithologist! It is not often that I can come across the same types of colleagues (R developers and ornithologists) at the same conference, so I cherish these experiences.

Before I came to Ropsci, I started my professional career as Behavioral ecologist and ornithologistStudying the effects of urban sound and habitat on communication in Chickadian (Tits for the non-Noord-Americans). While I have shifted to r consulting and supporting Good Here at Ropenci with our great community, nowadays I still work mainly for other ornithologists or non-profit organizations with bird-related nature conservation.

This means that the Society for Canadian ornithologists Is still very much my ‘home’ organization and I am always enthusiastic to go to meetings and to make contact with my colleagues again. But the ornithology conference or not, I always try to bring a little r, open science and cropci to the meeting.

In the past I have organized symposia on topics such as ” R for ornithologists: Perspectives from users to programmers (against birdwatchers)”Or” How can ornithologists find R -Packages?“, And helped to have workshops on R -Packages for Ornithology (such as Bbsbayes2).

This year I felt that I had to go a little further than R and decided to talk about ” Practical tips for open science in Ornithology“My goal was to encourage ornithologists (or other scientists) to try open science. To realize that it does not require background in computer science, or buckets with money! And because ornithology has many scientists who already have open data, open methods and open science, to share some ideas for doing more of their colleagues.

For the ROPSCI community this can feel “back to basic”. The conversations we have are more often about how you can be better With open science? How can you make that study complete Reproducible? How can we improve Open code quality^?

But I think we sometimes forget that, in addition to time, skills and sometimes financing, Open science practice requires a lot of courage^.

For those who have just started (such as students), or people without open science (such as researchers from small institutions), practicing open science may seem overwhelming and extremely intimidating. It is scary to think about the criticism if you “do not do science law”, or the consequences if you make a mistake.

I wanted to concentrate on baby steps, to make it clear that it makes the effort that is important, not to get perfect!

So in addition to some practical advice, I gave four general tips:

1. Try not to do everything

   • Be nice for yourself
   • You can grow smart and grow!

2. Do a new thing

   • Try to expand your skills for each project, learn a new thing

3. It’s okay to be nervous

   • Errors happen, remember that by practicing open science, you are already great!

4. Work with others together

I think that giving this conversation best was the number of students who approached me afterwards, excited (and nervous) to share their code online. Full of questions from practical about the use of Github for general about how ‘good’ your code must be shared. My answer to this last question was: “If you used it, share it. (But annotate as crazy!)”

What are your favorite tips for encouraging open science?

Recognition

Thanks Alex Koiter For ideas and brainstorming for my speech, as well as for his great (and much longer) talk, Open and reproducible soil science.

Related