What does it mean, in science, to be open?
I don’t know.
I wrote a while back, that while I endorse the principles of ‘openness‘, I struggle with the issue of ‘how‘. Since then I have been trying to listen and learn. [Or, better said, shut up and listen.] I started trying to see what hurdles I encountered trying to work exclusively on Open Source Software. I joined the Learning4Content course at WikiEducator. I started looking into platforms that would fit my needs as an open lab notebook. I tried to follow the Open Science Summit. I listened hard at sessions at SciFoo Camp. I went to some New Zealand open data discussions. I became an Academic Editor at PLoS ONE. I joined the panel of the Creative Commons Aotearoa New Zealand.
And after several months of ‘listening’ the one thing that keeps popping in my head is:
kubke, you ain’t gonna figure it out by yourself.
The loudest message that I heard is, perhaps, that there is not a single, simple, one-size-fits-all answer, and that it just may come down to fumbling through until we figure it out.
So, I decided to fumble.
I am taking in Summer students this summer to work on a project that I will try to make as ‘open’ as possible.
I am leaning towards a few things:
- I am pretty sure I want to give Mahara a go as a platform for the day-to-day ‘lab’ stuff.
- I am pretty sure I want to regularly put as much as I can into my space in OpenWetWare.
- I am pretty sure I want to try to shift my imaging to Open Source Software (e.g., Osirix, ImageJ, Cell Profiler)
- am pretty sure I want to put the work out there as it is being gathered.
What I am not so sure about is how this will work. It will be a steep learning curve, but one thing that I am hoping is that by giving it a go I may begin to get the answers.
And hopefully some of the smart people out there might give me a hand and help me steer the boat in the right direction.