Torchbearers for open data are nudging us incrementally closer to an ideal open access world. But there are other key players as well as researchers – programmers, data managers, and trainers. Ayushi Sood met some at Springer Nature’s Better Science Through Better Data (#scidata17) 2017 conference.
The 2017 Better Science through Better Data conference, held in October, was revealing and eye-opening in more ways than one. Lightning talks and keynote speeches by speakers from the global scientific community highlighted the mosaic of data sharing protocols, policies and success stories. Even more interesting than the talks were the people giving them – spirited contributions by researchers, programmers, publishers, law experts and data managers highlighted how different professionals occupy their own niches in the open data world and help the community to grow.
The obvious first candidates to participate in and benefit from open scientific data are the people generating and using the data – researchers themselves. Adam Kucharski, an assistant professor at the London School of Hygiene and Tropical Medicine, showcased data sharing models for modelling Ebola epidemics across Africa, while Debbie Baynes, a data centre scientist at the European Space Astronomy Centre in Madrid, unveiled a free tool to look at the night sky through the world’s telescopes. These and many more other speakers are the torchbearers open data needs – people in the field, implementing small yet crucial steps in their research workflow to bring us incrementally closer to an ideal, open-access world. They form the backbone, the strong core of the open scientific data milieu.
These people are only a part of the picture, though. In a data-sharing ecosystem, the frameworks which grow around and support the researcher are built by programmers, data managers, and trainers who design and implement the tools an open lab requires. With the reproducibility crisis in science coming to a head, more and more software developers are working on facilitating open research. Two of the major software tools showcased at #scidata17 were Code Ocean, a cloud based computational reproducibility platform, and the Dat project. This video of Danielle C Robinson’s conference presentation (Robinson is is scientific and partnerships director at non-profit Code for Science and Society), explains more about Dat:
Jez Cope, a librarian and research data manager at the University of Sheffield, UK, emphasised the need for active leadership by librarians in research data management in his keynote. Developing open data tools can be a highly rewarding endeavour in itself- just ask conference speakers Kirstie Whitaker (research fellow at the Alan Turing Institute), Bruno Vieira (a PhD student at Queen Mary University London) and Danielle C Robinson, all of whom are 2016 Mozilla Science Lab Fellows, awarded for their work in open science.
At a larger scale, open data and open access in general brings with it some uncomfortable questions about intellectual property, competition and privacy. While the scientific world moves towards greater public outreach and openness to combat increasing mistrust of science, the legal and licensing world must move in step. Arul George Scaria, assistant professor at the National Law University in Delhi, shared crucial insights on the Indian research community’s closed-mindedness towards open data, and how many of the problems plaguing Indian science may be tackled with a fresh approach towards patenting and innovation. Aled Edwards, co-founder and CEO of the Structural Genomics Consortium, a public private partnership, went a step further by suggesting patents in science be done away with as a whole, arguing that they hold back innovation rather than spurring it on.
At an institutional level, open data and transparency in science must be supported by publishers and grant funding agencies. The obvious way to show support for open data, as Magdalena Skipper, Editor in Chief of Nature Communications put it, is to incentivise data sharing by giving preference to studies following FAIR (Findable, Accessible, Interoperable, Reusable) data principles in both funding opportunities and paper acceptance in prestigious journals. The Wellcome Trust has taken the first step in requiring its grant awardees to have open data in their studies. While we wait for the inevitably slow change to seep through to other established institutions, though, smaller changes like transparent peer review can be adopted right now- as has been done by f1000research.com, a journal which is now ‘open’ in every sense of the word. Publishers and policymakers can therefore start small towards open data, knowing every bit matters.
One of the biggest takeaways of #scidata17 was the richness of knowledge and variety of skills in the open data community. Open research data is not just something scientists have to work at- it is something you and I can contribute our skills towards. A robust open data ecosystem cannot spring out of nowhere- it has to be built with the synergy of programmers, data scientists, researchers, lawyers, and policymakers. While researcher-led efforts may get us to a point where a larger proportion of data is open, it is only with an organic, ground-up approach incorporating the wider milieu that open science will become the new standard worldwide.
Ayushi Sood is an undergraduate microbiology student at Amity University, India. Her interest in what makes life tick made her fall in love with bacteria and astrobiology, and her passion for making scientific research more efficient and accessible led her to explore bioinformatics. She has been a part of research projects investigating nanoparticle-plant interactions, transgenic algae, and bacteria-algae associations. Ayushi enjoys dance, writing, and functional DIY craft. You can follow her work on Bitesize Bio and connect with her on LinkedIn or Facebook.