Follow the Panton Principles to ensure your data is licensed and accessible for immediate reuse, says Atma Ivancevic.
In a world where scientific discovery is driven by impact factor and funding, the idea of open data may seem idealistic. But the open data movement has been growing since the early 2000s, spurred by the rise of big data and computational capabilities. For the sake of reproducibility in science, we need to encourage data sharing after publication.
Founders of the Panton Principles at the Panton Arms, Cambridge UK.
Copyright Panton Principles Authors (CC by 3.0).
Last year, Scientific Data and Springer Nature partnered with the Wellcome Trust to organize scidata16: presenting open science advocates from diverse fields; from cancer genomics to neuroscience to synthetic biology. We learned that open science can benefit your research and your career. Many people, including me, left the conference inspired to change their data practices. Good intentions aside, is there a right way to make data ‘open’?
In my last post, I reviewed Dr Jenny Molloy’s thoughts on data management. She used an example of a PhD student losing their rucksack – and five years of research data – as compelling reason to make regular back-ups. The rucksack in question was lost in 2011 at the Panton Arms pub in Cambridge. Little did our unfortunate student know that, just one year earlier, the same pub was made famous as the birth place of the Panton Principles: a set of guidelines for archiving your data.
The Panton Principles are based on the idea that scientific advancement requires constant scrutiny and recycling of resources in different ways. The original founders, led by Peter Murray-Rust, a chemist at the University of Cambridge, believed that research data should be available to anyone with a working internet connection. Their principles act as guidelines to show scientists how best to put data online, advertise and claim credit for it.
The first, and perhaps most important principle is to be clear about your intentions. People are more likely to use your data if they know it’s there, and freely available. Be precise: explicitly state your expectations in regards to reuse. If you want to be credited for results that come from your data, say that – and provide a suitable citation. As a bonus, follow it up with an open access web button pointing towards the download. For example:
The following data is freely available for any user to download, copy, distribute, adapt and build on. For publications that arise from the use of this data, please cite accordingly:
Contributors’ names (last edited date). Title of resource. Retrieved from https://webaddress on date-of-retrieval.
This statement can be added to your publication, in a data repository, on your university website and even on your personal blog. Advertise well to reap the rewards.
Second, use a data-appropriate license. Creative Commons (CC) is a commonly used public copyright license for content such as images, text and audio-visual materials. But it was not designed for data. The Panton Principles provide a list of recommended licenses that conform to the open definition and are more suitable for collections of data.
The third principle discourages the use of restrictive clauses. Data that is completely open can be used and optimized freely for whatever purpose. Think carefully about whether you have a good reason for limiting commercial or non-commercial repurposing. If it is purely to stop your competitors from profiting, ask yourself whether that is worth hindering advancement of the field.
Finally, make sure that the data is placed in the public domain. This can be done by using a Public Domain Dedication and Licence (PPDL), or Creative Commons Zero Waiver (CCZero). For more information, see the protocol for implementing open access data.
Simple, right? Four quick steps, and then you’re free to take a hard-earned break while researchers across the globe repurpose your data.
Atma Ivancevic is a neuroscience postdoc moonlighting as a freelance writer. During the day, she works at the Women’s and Children’s Hospital in Adelaide, Australia, using bioinformatics to investigate neurological disorders. Outside of work, she enjoys cycling and aerial gymnastics. You can follow her on Twitter, ResearchGate or LinkedIn.
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