This text is based on a short presentation I gave in a webinar organized by Open Access Academy, EURODOC and FOSTER today, titled Open Data – How, Why and Where? I was asked to speak about why early career researchers should care about open data.
Sometimes I wonder whether we are doing ourselves a disservice by talking about Open Access, Open Data, Open Science, Open Source, Open Notebook Science etc. All of these labels make openness seem like something new, something complicated and something that adds to the burden of researchers, when it is exactly the opposite. To me Open Science is just plain good science, both in terms of academic excellence and research integrity.
Open Access and Open Data are already reality. More and more funders expect that scientific publications done with their support are openly available for maximum impact. Policies are not yet as demanding for research data, but there is an increasing amount of incentives and pressure to make it more openly available too.
In light of this, you don’t need me to tell you that you should care about open data. What I can tell you instead is why you should embrace and practice open data, even go beyond it.
What I’m trying to do with my dissertation is to go beyond open access and open data and make open the default setting of my work. It makes life so much easier compared to the other option.
When I got the research grant I’m currently working on I wanted to put into practice the things I had been trying to advance in my previous job as the coordinator at the Open Science and Research Initiative by the Finnish Ministry of Education.
I tried to dissect my research to make it fit into boxes labeled Open Access, Open Data, Open Methods and so on. It felt forced. None of the policies seemed to apply to my particular case. I didn’t even understand what the word data meant for me: I use non-digital archival sources (that means paper), published books (more paper), statements and guidelines and also collect interview and survey data.
When I asked myself “What can I publish as Open Data?” I hit a wall: nothing.
Nothing that I produce or can produce fill out the requirements of for example the Open Knowledge Foundation’s definition of open data. But instead of giving up and just drawing the conclusion that qualitative social scientific research will forever be a bystander in the Open Science discussions I wanted to find a different approach.
So I rephrased the question asking “What can I NOT publish openly?”. This way I don’t have to justify openness and worry about doing it right according to this or that policy. This new attitude has removed the fear of not fitting in and given me a clear direction. I can concentrate on doing the most interesting research I can, as transparently I can, on my own terms.
There is of course a lot of work to be done and things to figure out, like ethical issues, tools, platforms, formats, metadata, you name it. Fortunately there is a great community out there, ready to give support.
I want to stress that being open by default doesn’t mean being careless. I can do trial and error with my own life but not with the lives of my research subjects. That’s why I will keep on asking the question until my research is finished and keep on getting different answers in different phases of the process. I have put a lot of effort into planning my work and will continue to do so. Whenever I am in doubt about publishing something I’ll take a time-out and proceed only when I can be sure of not harming anyone.
To summarize why you should make openness your default setting:
don’t just passively wait what kinds of demands the funders and other makers of research policy will impose on us next, be pro-active and create your own practices
be a member of the open science community
do good science that has real impact
advance your career: more and more recruiters and funders take into account published data, you can also gain traditional merit via citations that your open access articles and published data sets generate
stop being afraid of failure: you’d be surprised how many people are interested in your non-significant results, reducing publication bias is also an ethical issue
you might not be in the academia for ever, so build broad expertise and a personal brand