What do you see as the greatest advantages of Open Science?

Lars Arvestad. Foto: Privat.

– Improved accessibility to research results, which benefits everybody, even us who sit in well-to-do areas with access to a good library. When data start being shared, and not just articles presenting analyses of the data, the dynamic of research changes. It becomes possible for people other than the authors to quickly and easily begin to investigate the data.

It also creates the opportunity to spot mistakes, negligence and fraud. Presumably it will be more difficult to cheat when data are expected to be accessible.

What kinds of practical applications within Open Science do you see as the most meaningful for good research practice?

– For me open repositories are the most important. For molecular biology and related fields, it’s been fantastic that journals have required you to deposit your DNA and protein sequences in order to publish. What we need now is to change the norms so that we expect more types of data to be deposited and that more fields follow suit and begin to require accessible data.

What do you see as the greatest challenges in practicing Open Science?

– One challenge is education – that the principles of openness be perceived by more people as simple and natural to follow. Right now there are numerous details one has to consider when publishing, and it would be preferable to avoid having even more instructions about data deposition.

What changes within research politics and the research community could counter these challenges?

– I think the most important thing is that researchers engage themselves in the topic. Open Science as a grass roots movement is quite old, and it’s growing in strength. Universities and politicians can and should support it, of course, but it is the actions of the researchers which will have the greatest impact.

How and when should teaching about Open Science take place?

– Today it is good to start with PhD students. Sometimes the mentorship of a supervisor is enough, but a selection of courses could allow us to spread knowledge about Open Science into areas where it does not already have strong adherents.

Programming and data analysis are also fertile grounds, and there I think there’s much to do already at the BA level. Everyone who completes a BA programme within the natural sciences, for example, should be able to code, and that’s not how it is today.

Do you have any concrete examples – positive or negative – of where Open Science applications have made a difference in practice?

– I think there are several positive examples within my field of bioinformatics. For example, when someone evaluates computer programs and methods, nowadays the reference data used are always published. Those who want to publish a new method for an old problem can easily locate reference data to use without even having to contact the people who published those data.

It makes a difference, because the entire process goes quicker, and one isn’t dependent upon an individual researcher’s goodwill or data management either. Fifteen years ago, when a colleague and I wanted to test an idea, it happened that the method we wanted to compare it to was no longer runnable on a modern computer, and we learned that its test data had been lost in a drive crash. Problems of this kind are decidedly less common today.