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

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Dealing with Data 2019 (January 2020): Collaboration Across the Nations

Picture the scene: A cold January day, the wind blowing the scarves of the passers-by through the large windows of the Informatics Forum meeting room. The group inside listens, takes notes, tweets, and asks questions of the speakers, representing a range of disciplines across the University…

Dealing with Data is an annual event hosted by the Research Data Service. Its aim is to engage the University community of researchers and support professionals around a theme, to share success stories and challenges in the myriad, everyday issues involved with data-driven research. The theme this year reflected the difficulty of managing research data in large, collaborative projects. Due to industrial action, the original November event was postponed to January. Around a hundred researchers – staff and students – participated, along with support staff who gave lightning talks about research-focused services. Full presentations and videos are now available.

So Benjamin Bach, our keynote speaker, inspired us with state of the art data visualisation software and techniques for both exploration and presentation. But he also illustrated the difficulties of portraying all of the data in all of its facets of a rich dataset, and the consequences of making necessary choices for its interpretation.
The first session began with Tamar Israeli’s study of researchers’ use of collaborative and institutional tools showed the challenges of making local infrastructure user friendly enough to attract new users familiar with slick cloud-based services. Then Mark Lawson demonstrated his ingenuous ‘ethical hacking’ to piece together a set of APIs to create a research workflow for samples and images for histology research. Minhong Wang conveyed a higher level view of data management focused not just on data-driven, but knowledge-driven phenotyping.

Next were the lively lightning talks, in which Mike Wallis of Research Services warned of a new Digital Dark Age, and David Creighton-Offord spoke of the dillemmas in Information Security user support where shiny doesn’t always equal safe. Lisa Otty spoke of innovative training and text mining projects bringing data science to the Humanities, and Rory MacNeil demonstrated how the RSpace electronic lab notebook can connect to a host of popular open science tools.

Following a lively lunch with chat between delegates and with hosts of the service exhibitions, Alex Hutchison showed a highly programmatic view of data management and ethics control from the UNICEF collaboration, in collecting and analysing real world data about children in need. Caileen Gallagher offered a case study of how food courier data could be used to empower workers. Sanja Badanjak shared her data integration problems of peace agreements around the world, conveying both innovative solutions and time-consuming workarounds.

In the final session Edward Wallace brought in the Edinburgh Carpentries to the rescue of poor data skills within Biological Sciences and the wider University – itself a great example of cross-community collaboration building a community of trainers. Gillian Raab showed us how any data problem however intractable can be solved by resourcefulness and determination, making use of DataShield for multi-party computation when datasets are too sensitive to be shared. Johnny Hay and Tomasz Zielinski demo’d their Plasmo ‘boutique repository’ for plant-systems biology modelling and Holly Tibble described tackling an international collaboration in linking administrative datasets via ‘ridiculously detailed’ statistical analysis plans. Representing the Research Data Service, I wrapped up proceedings with some of these very observations.
Both presentations and videos are available.

Welcome

  • Jeremy Upton, Director of Library and University Collections. [Presentation]

Keynote

  • Data Visualization for Exploration and Presentation, Prof. Benjamin Bach. Lecturer in Design Informatics and Visualization. [Presentation] [Slides]

Session 1 – Chair: Theo Andrew

  • “Data Something”: Assessing Tools, Services and Barriers for Research Data Collaboration at the University of Edinburgh – a small-scale study carried out by Dr Tamar Israeli with support from the Research Data Support team. Robin Rice – Data Librarian & Head of Research Data Support Services. [Presentation] [Slides]
  • Integrated secure web application to deliver centralised management of research samples, histology services and imaging data. Mark Lawson, Data & Project Manager, MRC Centre for Reproductive Health, QMRI. [Presentation] [Slides]
  • Building the Knowledge Graph for UK Health Data Science Minhong Wang et. al, Deanery of Molecular, Genetic and Population Health Sciences. [Presentation] [Slides]

Session 2 – Chair: Kerry Miller

  • The Data Opportunities & Challenges when Collaborating across Organisations
    Alex Hutchison, Delivery Director – Data for Children Collaborative with UNICEF. [Presentation] [Slides]
  • Restoring Gig Workers to Power: Personal Data Portability, Supply of Digital Content and Free Flow of Data in the European Data Economy. Cailean Gallagher, Scottish Trades Union Congress, & St Andrews University Institute of Intellectual History. [Presentation] [Slides]
  • Dealing with data in peace and conflict research. Sanja Badanjak, Postdoctoral Research Fellow, School of Law. [Presentation] [Slides]

Session 3 – Chair: Robin Rice

  • Bringing researchers to data: computing skills training with Edinburgh Carpentries.
    Edward Wallace, Sir Henry Dale Fellow, Institute of Cell Biology. [Presentation] [Slides]
  • Running an analysis of combined data when the individual records cannot be combined. Gillian M Raab and Chris Dibben, Scottish centre for Administrative Data Research. [Presentation] [Slides]
  • The grant is dead, long live the data. Johnny Hay and Tomasz Zieliński, School of Biology, University of Edinburgh. [Presentation] [Slides]
  • International collaborations using linked administrative data: Lessons from the MARIC study. Holly Tibble, Usher Institute, University of Edinburgh. [Presentation] [Slides]

Robin Rice
Data Librarian and Head, Research Data Support
Library & University Collections

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‘Protecting sensitive data’: new MANTRA unit now available

The Research Data Support team are pleased to announce a new update to MANTRA, the free and open online research data management training course.

The new ‘Protecting sensitive data’ module has been created from scratch, replacing the previous ‘Data protection, rights and access’ unit to provide an up-to-date guide for researchers working with sensitive and personal data.

MANTRA is designed to give post-graduate students, early career researchers, and information professionals the knowledge and skills needed to work effectively with research data.

The ‘Protecting sensitive data’ unit considers the ethical and legal contexts for conducting research with sensitive data, including information and guidance on:

  • What makes data sensitive?
  • What UK and European data protection laws mean for research
  • Research ethics, informed consent and consent documentation
  • Approvals processes and accessing restricted data
  • Safeguarding sensitive data, including data retention limits, access controls and anonymisation
  • Data protection training

MANTRA is designed to be approachable and informative, and incorporates text and video content plus quizzes, interactive exercises and a ‘further reading’ section.

We hope you find the new content interesting and useful, and we welcome comments on the new unit, as well as feedback on the other seven MANTRA modules.

Finally, the RDS team are currently working on a series of further updates to MANTRA which will be rolled out over the coming weeks, and information about these releases will be posted on this blog and the RDS Twitter account.

Bob Sanders

MANTRA, Lead Editor

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Research data management in a time of quarantine

Covid-19 has shaken up our world, and disrupted University life as we know it. But in terms of a silver lining, it has provided opportunities for open data / open research to prove their worth, in the search for a vaccine and other approaches to managing and treating the complications of the virus. SPARC Europe have collected a number of case studies on Open Science and the Coronavirus. If you’ve been working on Coronavirus research here at Edinburgh, we’d love to hear from you, especially if there is anything we might be able to do to help. So far we have engaged with researchers in all three Colleges studying, or hoping to study, an aspect of COVID-19; about handling sensitive data, archiving or sharing relevant data, or bidding for new research.

How has it affected us in Research Data Support?

  • We are all working from home, although some of us have unavoidable childcare responsibilities which may slow down responses;
  • In terms of answering Research Data Management (RDM) enquiries it’s business as usual. UniDesk has been a little quieter than usual, but we are receiving more complex queries as researchers adjust to the new reality;
  • Data Management Plan (DMP) assistance is business as usual, and we are now set up on Teams for video consultations – let us know if you’d be interested in one of these;
  • During the lockdown we will be refreshing our existing Research Data MANTRA training and directing research staff and students to this resource in place of our face-to-face training, which has been temporarily suspended. If you have a question or would like to discuss any aspect of RDM or Data Management Planning please contact the team using data-support@ed.ac.uk to setup an online consultation.

From the researcher’s point of view, in some cases collecting and processing or analysing new data may be more difficult than it usually is, and in many cases impossible without access to lab equipment or direct contact with research subjects. So why not turn your attention to other elements of RDM, such as preparing older data for deposit, and linking it with your published research papers to fortify the scholarly record?

What can you do?

  • Use the time away from the lab or the field to tidy up data you’ve already collected or created (and don’t forget to attach metadata/contextual information!);
  • Deposit completed data in DataShare (or a disciplinary repository, with metadata recorded in Pure);
  • If you have deposited in DataShare before, check the usage stats and AltMetrics feed to see whether it has been used by others;
  • Create an ORCID (unique, persistent global researcher’s ID), and link it with your Pure account to ensure you stay linked with your outputs throughout your career;
  • Invite us to comment on your DMP, or get in touch about anything else RDM-related;
  • Let us know if you’d like to arrange any bespoke training or awareness-raising sessions;
  • Take some or all of the MANTRA course and let us know if you have any comments.

Martin Donnelly
Research Data Support Manager
Library and University Collections

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