Research Data Management Training for University of Edinburgh staff and students, Spring 2019

Following on from our blog post on the benefits of RDM training which was posted on the 15th of November, we have scheduled our in-person training courses for the Spring 2019 semester. A description of each course and its intended audience can be found on our Training and support resources webpage, alongside details of online training offerings. Courses can usually be booked through MyEd Event Booking approximately four weeks beforehand.

Course Dates & Times Location
Creating a Data Management Plan 16/01/2019@10:30-12:30 Seminar Room 3, Chancellor’s Building (Little France) Map
28/02/2019@14:00-16:00 Murchison House, Room G.12 (Kings Buildings) Map
27/03/2019@14:00-16:00 Appleton Tower, Room 2.07 (Central Area) Map
Working with Personal and Sensitive Data 13/02/2019@14:00-16:00 Seminar Room 3, Chancellor’s Building (Little France) Map
21/03/2019@10:00-12:00 G.69 Joseph Black Building (Kings Buildings) Map
01/05/2019@14:00-16:00 High School Yards, Classroom 4 (Central Area) Map
Good Practice in Research Data Management 24/01/2019@13:30-16:30 Murchison House, Room G.12 (Kings Buildings) Map
22/02/2019@ TBC TBC
05/03/2019@13:30-16:30 EW11, Argyle House, 3 Lady Lawson Street (Central Area) Map
05/04/2019@09:30-12:30 Seminar Room 6, Chancellor’s Building (Little France) Map
Managing Your Research Data 17/01/2019@10:00-12:00 Room B.09, Institute for Academic Development, 1 Morgan Lane, (Holyrood) Map
05/02/2019@10:00-12:00 Lister Learning and Teaching Centre – Room 1.3 (Central Area) Map
15/03/2019@10:00-12:00 Seminar Room 5, Chancellor’s Building (Little France) Map
12/04/2019@10:00-12:00 Room B.09, Institute for Academic Development, 1 Morgan Lane, (Holyrood) Map
25/04/2019@14:00-16:00 G.69 Joseph Black Building (Kings Buildings) Map
18/06/2019@10:00-12:00 Room B.09, Institute for Academic Development, 1 Morgan Lane, (Holyrood) Map
Handling Data Using SPSS 12/02/2019@13:30-16:30 Room 1.08, First Floor, Main Library, George Square (Central Area) Map
02/04/2019@13:30-16:30 EW10, Argyle House, 3 Lady Lawson Street (Central Area) Map
Data cleaning with OpenRefine 07/02/2019@13:30-16:30 Lister Learning and Teaching Centre ,2.14 – Teaching Studio, (Central Area) Map

Kerry Miller
Research Data Support Officer
Research Data Service
Library and University Collections

 

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Personal data: What does GDPR mean for your research data?

It falls upon me to cover the ‘hot topic’ of research data and GDPR (European privacy legislation) just before a cold winter holiday break. This makes me feel like the last speaker in a session that has overrun – ‘So, I’m the only thing between you and your lunch …’ But none of this changes the fact that the General Data Protection Legislation – codified into British Law by the UK Data Protection Act, 2018 – is a very important factor for researchers working with human subjects to take into account.

This is why the topic of GDPR and data protection arose out of the case studies project that my colleagues completed this summer. This blog post introduces the last in the series of these RDM case studies: Personal data: What does GDPR mean for your research data?

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Dr. Niamh Moore talks about how research has evolved to take data protection and ethics into account, focusing on the time-honoured consent form, and the need to take “a more granular approach” to consent: subjects can grant their consent to be in a study, but also to have their data shared–in the form of interview transcripts, audio or video files, diaries, etc., and can choose which of these they consent to and which they do not.

Consent remains a key for working with human subjects ethically and legally, but at the University of Edinburgh and other HEIs, the legal basis for processing research data by academic staff may not be consent, it may simply be that research is the public task of the University. This shifts consent into the ethical column, while also ensuring fair, transparent, and lawful processing as part of GDPR principles.

I was invited to contribute to the video as well, from a service provider’s perspective because our Research Data Support team advises and trains researchers on working with personal and sensitive data. One of my messages was of reassurance, that actually researchers already follow ethical norms that put them in good stead for being compliant with the Law.

Indeed, this is a reason that the EU lawmakers were able to be convinced that certain derogations (exceptions) could be allowed for in “the processing of personal data for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes,” as long as appropriate safeguards are used.

Our short video brings out some examples, but we could not cover everything a researcher needs to know about the GDPR – the University of Edinburgh’s Data Protection Officer has written authoritative guidance on research and data protection legislation for our staff and students and has also created a research-specific resource on the LEARN platform. Our research data support team also offers face to face training on Working with Personal and Sensitive Data which has been updated for GDPR.

I have tried to summarise how researchers can comply with the GDPR/UK Data Protection Act, 2018 while making use of our Research Data Service in this new Quick Guide–Research Data Management and GDPR: Do’s and Don’ts. Comments are welcome on the usefulness and accuracy of this advice!

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

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Dealing With Data 2018: Summary reflections

The annual Dealing With Data conference has become a staple of the University’s data-interest calendar. In this post, Martin Donnelly of the Research Data Service gives his reflections on this year’s event, which was held in the Playfair Library last week.

One of the main goals of open data and Open Science is that of reproducibility, and our excellent keynote speaker, Dr Emily Sena, highlighted the problem of translating research findings into real-world clinical interventions which can be relied upon to actually help humans. Other challenges were echoed by other participants over the course of the day, including the relative scarcity of negative results being reported. This is an effect of policy, and of well-established and probably outdated reward/recognition structures. Emily also gave us a useful slide on obstacles, which I will certainly want to revisit: examples cited included a lack of rigour in grant awards, and a lack of incentives for doing anything different to the status quo. Indeed Emily described some of what she called the “perverse incentives” associated with scholarship, such as publication, funding and promotion, which can draw researchers’ attention away from the quality of their work and its benefits to society.

However, Emily reminded us that the power to effect change does not just lie in the hands of the funders, governments, and at the highest levels. The journal of which she is Editor-in-Chief (BMJ Open Science) has a policy commitment to publish sound science regardless of positive or negative results, and we all have a part to play in seeking to counter this bias.

Photo-collage of several speakers at the event

A collage of the event speakers, courtesy Robin Rice (CC-BY)

In terms of other challenges, Catriona Keerie talked about the problem of transferring/processing inconsistent file formats between heath boards, causing me to wonder if it was a question of open vs closed formats, and how could such a situation might have been averted, e.g. via planning, training (and awareness raising, as Roxanne Guildford noted), adherence to the 5-star Open Data scheme (where the third star is awarded for using open formats), or something else? Emily earlier noted a confusion about which tools are useful – and this is a role for those of us who provide tools, and for people like myself and my colleague Digital Research Services Lead Facilitator Lisa Otty who seek to match researchers with the best tools for their needs. Catriona also reminded us that data workflow and governance were iterative processes: we should always be fine-tuning these, and responding to new and changing needs.

Another theme of the first morning session was the question of achieving balances and trade-offs in protecting data and keeping it useful. And a question from the floor noted the importance of recording and justifying how these balance decisions are made etc. David Perry and Chris Tuck both highlighted the need to strike a balance, for example, between usability/convenience and data security. Chris spoke about dual testing of data: is it anonymous? / is it useful? In many cases, ideally it will be both, but being both may not always be possible.

This theme of data privacy balanced against openness was taken up in Simon Chapple’s presentation on the Internet of Things. I particularly liked the section on office temperature profiles, which was very relevant to those of us who spend a lot of time in Argyle House where – as in the Playfair Library – ambient conditions can leave something to be desired. I think Simon’s slides used the phrase “Unusual extremes of temperatures in micro-locations.” Many of us know from bitter experience what he meant!

There is of course a spectrum of openness, just as there are grades of abstraction from the thing we are observing or measuring and the data that represents it. Bert Remijsen’s demonstration showed that access to sound recordings, which compared with transcription and phonetic renderings are much closer to the data source (what Kant would call the thing-in-itself (das Ding an sich) as opposed to the phenomenon, the thing as it appears to an observer) is hugely beneficial to linguistic scholarship. Reducing such layers of separation or removal is both a subsidiary benefit of, and a rationale for, openness.

What it boils down to is the old storytelling adage: “Don’t tell, show.” And as Ros Attenborough pointed out, openness in science isn’t new – it’s just a new term, and a formalisation of something intrinsic to Science: transparency, reproducibility, and scepticism. By providing access to our workings and the evidence behind publications, and by joining these things up – as Ewan McAndrew described, linked data is key (this the fifth star in the aforementioned 5-star Open Data scheme.) Open Science, and all its various constituent parts, support this goal, which is after all one of the goals of research and of scholarship. The presentations showed that openness is good for Science; our shared challenge now is to make it good for scientists and other kinds of researchers. Because, as Peter Bankhead says, Open Source can be transformative – Open Data and Open Science can be transformative. I fear that we don’t emphasise these opportunities enough, and we should seek to provide compelling evidence for them via real-world examples. Opportunities like the annual Dealing With Data event make a very welcome contribution in this regard.

PDFs of the presentations are now available in the Edinburgh Research Archive (ERA). Videos from the day will be published on MediaHopper in the coming weeks.

Other resources

Martin Donnelly
Research Data Support Manager
Library and University Collections
University of Edinburgh

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New video: the benefits of RDM training

A big part of the role of the Research Data Service is to provide a mixture of online and (general/tailored) in-person training courses on Research Data Management (RDM) to all University research staff and students.

In this video, PhD student Lis talks about her experiences of accessing both our online training and attending some of our face-to-face courses. Lis emphasises how valuable both of these can be to new PhD candidates, who may well be applying RDM good practice for the first time in their career.

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It is interesting to see Lis reflect on how these training opportunities made her think about how she handles data on a daily basis, bringing a realisation that much of her data was sensitive and therefore needed to be safeguarded in an appropriate manner.

Our range of regularly scheduled face-to-face training courses are run through both Digital Skills and the Institute of Academic Development – these are open to all research staff and students. In addition, we also create and provide bespoke training courses for schools and research groups based on their specific needs. Online training is delivered via MANTRA and the Research Data Management MOOC which we developed in collaboration with the University of North Carolina.

In the video Lis also discusses her experiences using some RDS tools and services, such as DataStore for storing and backing-up her research data to prevent data loss, and contacting our team for timely support in writing a Data Management Plan for her project.

If you would like to learn more about any of the things Lis mentions in her interview you should visit the RDS website, or to discuss bespoke training for your school or research centre / group please contact us via data-support@ed.ac.uk.

Kerry Miller
Research Data Support Officer
Library and University Collections
The University of Edinburgh

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