Protocols.io trial… six months on!

We launched a trial of protocols.io Enterprise in December 2019, and a lot has been achieved in the first six months.

The number of registered UoE users has increased from 121 to 217 and the number of private protocols from 36 to 106 which demonstrates a significant interest in using the platform with its additional Enterprise functionality,

We have also run a number of webinars specifically for UoE staff and students which have been well attended.

While these numbers suggest interest amongst our research community in using protocols.io we have to collect better feedback before we can decide if protocols.io Enterprise is to become an ongoing service provided by the University.

That is why we are now launching this short survey about protocols.io which is open to all UoE research staff and students. The aim is to gather initial thoughts from our community and to identify people who may be prepared to contribute more in-depth feedback as the trial progresses.

The survey can be accessed at https://edinburgh.onlinesurveys.ac.uk/protocols-io-6-month-survey

To find out more about protocols.io or this trial you can read this blogpost from when the trial launched: https://libraryblogs.is.ed.ac.uk/2019/12/13/new-research-data-management-tool-on-one-year-trial-protocols-io/

Alternatively please visit our website, where you will also find links to all the protocols.io webinars we have run: https://www.ed.ac.uk/information-services/research-support/research-data-service/during/open-research-tools/protocols

Kerry Miller
Research Data Support Officer
Library & University Collections

Two new Quick Guides for good Research Data Management

The Research Data Support team have recently published two new Quick Guides, the latest in a series of short, user-friendly documents intended to help our research staff and students plan, manage and preserve their data effectively, safely, and for the long-term.

Quick Guide 5 takes the topic of “Open Research” – also known as Open Science, particularly in a European context. The drive towards research transparency and the removal of barriers to accessibility has gathered a great deal of momentum over recent years, to the extent that “Open by default” is an increasingly common approach. Open research enables scientific findings to be tested, reproduced and built upon far more quickly than traditional approaches allowed. The benefits of Open Research are being demonstrated in real time, right in front of our noses, as researchers at Edinburgh tackle various aspects of the Covid-19 pandemic. We recently tweeted about one such project which examined the effectiveness of face coverings in reducing the range travelled by breath, which of course helps transmit the virus. The data underpinning this research is freely available to everyone via Edinburgh DataShare.

The latest Quick Guide, the sixth in the series, addresses the ‘FAIR’ principles, which state that research data should – so far as possible, and appropriate – be Findable, Accessible, Interoperable and Reusable. These principles emphasise machine-actionability (i.e. the ability of automated computational systems to find, access, interoperate, and reuse data with minimal or no human intervention) as humans increasingly rely on computational means to discover and work with data as a result of the increase in volume, complexity, and creation speed of data.

These two new publications join our existing guidance on topics such as the basics of Research Data Management (RDM), RDM and data protection, and research data storage options at the University. Future topics planned include conducting research safely online, FAIR approaches to research software, and an overview of the systems and services available at Edinburgh in support of Open Research. If there is a particular topic you would find useful, please get in touch with us via data-support@ed.ac.uk or the IS Helpline.

All of our Quick Guides can be found at https://www.ed.ac.uk/information-services/research-support/research-data-service/guidance

Martin Donnelly
Research Data Support Manager
Library and University Collections