Why do we do science?
I’m a scientist-in-training who enjoys learning about the intersection of science and society, so this is a very important question for me. In attempting to answer this question for myself, I’ve become more and more interested in the concept of Open Science (OS):
Open science is the movement to make scientific research, data and dissemination accessible to all levels of an inquiring society, amateur or professional.
I wanted to learn more about the philosophies behind OS, and the practical steps that scientists can take to make their work more open. I wanted to understand the benefits and drawbacks of open science. This post explores what I have learnt so far.
While there is a lot to learn, Open Science can be distilled into several core principles:
…to provide the public with unrestricted, free access to scholarly research—much of which is publicly funded. Making the research publicly available to everyone—free of charge and without most copyright and licensing restrictions—will accelerate scientific research efforts and allow authors to reach a larger number of readers.
— Budapest Open Access Initiative
Probably one of the best known, simplest, and most effective open principles. There are many different interpretations and implementations across publishers of scholarly works, but the core aim of OA is to remove restrictions on access (charges to view research) and use (copyright or licensing restrictions). Lisa Matthias made a great infographic showing the ways in which authors can make their work open access:
Open Data, Code, and Materials
Open data is data that can be freely used, re-used and redistributed by anyone – subject only, at most, to the requirement to attribute and sharealike.
— Open Data Handbook (taken from Open Definition)
Open materials (including data and code) are those which are made easily available in a convenient form, and which are licensed for re-use in a non-restrictive way. This enables other researchers and interested members of the public to build on other peoples work or incorporate datasets into their own work. There are many services to share data and materials (for example GitHub or FigShare).
Peer review is a cornerstone of the scientific method. It is the process by which professional peers are invited to critique the quality, novelty, and potential impact of research submitted for publishing. The dominant form of peer review has been criticised for being “slow, expensive, profligate of academic time, highly subjective, prone to bias, easily abused, poor at detecting gross defects, and almost useless at detecting fraud.” Open approaches to peer review emphasise the need to increase transparency, give reviewers credit for their work, and make more use of pre- and post-publication peer review.
There are two basic reasons to be concerned about making your research reproducible. The first is to show evidence of the correctness of your results. The second reason to aspire to reproducibility is to enable others to make use of our methods and results.
— Reproducibility in Science
In order to make research reproducible, we need to think about which parts of the work we make available and how this will effect other workers trying to reproduce our results. This could take the form of making code, software, and other materials freely available; by describing statistical methods in sufficient detail to reproduce the analyses; and by describing our overall methods as best we can. These approaches are especially important for computational research, but can be applied within any field. More details can be found here.
To conclude: A summary of what we can do to open up our science and have a greater impact with our work (click to see larger version):
Coming up in part II of this series: Science communication and open education resources.