Open Science Working Group activity focuses on three areas: open data, open access and open research. We build tools, apps, datasets and guidelines to facilitate all these aspects of open science.
Open ideas are gaining traction in many scientific communities where by default data is not shared freely, papers are published in closed access journals and the scientific process operates behind closed doors. The default level of openness varies across academic fields and therefore we seek involvement from researchers across the sciences and beyond to ensure these community norms are taken into account during projects.
relates primarily to the datasets associated with primary scientific literature. The current situation is inconsistent with regard to if and how such data is made available and terms of reuse are often unclear, scientists get little credit for sharing data so there is no incentive to put in the time required to make a dataset useful for other researchers. The working group penned Panton Principles for Open Data in Science recommend that all data arising from publicly funded research is made available under an open license and lay out the reasons why sharing good quality data is so important.
relates to full-text articles, which by default are published in subscription journals to which access costs a great deal for both institutions and individuals – up to $30 per article for non-subscription access. Great progress has been made by the OA movement in increasing OA publication rate so more science is freely available and not hidden behind a paywall, but this cannot be taken for granted. We recommend open access policies to funders and governments as well as building tools to maximise the impact and usefulness of OA research for a wide variety of end users.
encompasses the remainder of scientific research undertaken in the open, from keeping open lab notebooks, publishing open code and results to maximise reproducibility, open sharing of all data, through to involving citizens in research, particularly over the Internet through projects such as distributed computing e.g SETI@home and crowdsourced analysis of data e.g. tracking deforestation on ForestWatchers. We have collaborated with the Centre for Citizen Cyberscience to develop citizen science web tools such as this, powered by the open source pyBOSSA platform (see crowdcrafting.org) and we aim to continue work in this important and rapidly growing area.
Why are the three areas so important?
When combined, they can give rise to innovative, fast-paced and high quality science due to uninhibited access to resources and the ability to draw on expertise around the world. Some researchers are inhibited from continuing with their work due to the closed nature of the scientific literature, as well as negative attitudes among scientists with regard to data sharing. For example, in the the novel field of comparative MRI looking at the evolution of brain structures across diverse animals, datasets are extremely hard to obtain from researchers (Daniel Mietchen) and chemical informatics using large scale data and text mining of the literature is stimied by publishers who ban the use of text mining technologies and severely restrict the use of any results obtained in this manner (Peter Murray-Rust).
When these barriers are broken down, great progress can be made very rapidly:
- The Human Genome Project is a classic example of open sharing of data leading to incredible advances in biology in a short space of time.
- More recent projects such as Mat Todd’s Open Drug Discovery programme also show the value of open science. Thanks to a completely open approach with anyone welcome to take part via the internet and enthusiastically offered pro bono work from chemical companies, a preliminary solution to producing an improved drug against the neglected tropical disease schistosomiasis was achieved in less than a year. The group are now turning their attention to other diseases and are excited about demonstrating the value of open research while playing a part in alleviating major global health problems.
We hope to move towards a world where more such collaborations are possible, because openness means better science.
MRI Image from Wikimedia Commons under GFDL license.