Research Data Training – Semester 1

*UPDATE* – We have just added two new and exciting courses to our training schedule:

  • Assessing Disclosure Risk in Quantitative Data (RDS006)
  • Assessing Data Quality in Quantitative Data (RDS007)

To find out more about these courses just visit our training page.

Each semester the Research Data Support team puts together a training programme for researchers and research support staff in all schools, and at all points in their career. Our programme this year introduces a number of new courses, including one designed especially for Undergraduates planning their final year dissertation. We have also reviewed and refreshed all of our existing courses to ensure that they are not only up-to-date but also more engaging and interactive.

Full Course list:

  • Realising the Benefits of Good Research Data Management (RDS001)
  • Writing a Data Management Plan for your Research (RDS002)
  • Working with Personal and Sensitive Data (RDS003)
  • Data Cleaning with OpenRefine (RDS004)
  • Handling Data Using SPSS (RDS005)
  • Assessing Disclosure Risk in Quantitative Data (RDS006)
  • Assessing Data Quality in Quantitative Data (RDS007)
  • Data Mindfulness: Making the Most of your Dissertation (RDS009)
  • Introduction to Visualising Data in ArcGIS (RDS011)
  • Introduction to Visualising Data in QGIS (RDS012)

Full details of all these courses, with direct booking links, can be found on our training webpage https://www.ed.ac.uk/information-services/research-support/research-data-service/training

Courses can also be found and booked via the MyEd Events page.

We are always happy to deliver tailored versions of these courses suitable for a specific school, institute or discipline. Just contact us at data-support@ed.ac.uk to let us know what you need!

Kerry Miller
Research Data Support Officer
Library and University Collections

Announcing our new “Quick Guides” series

Earlier this week we bid farewell to our intern for the past four weeks, Dr Tamar Israeli from the Western Galilee College Library. Tamar spent her time with us carrying out a small-scale study on the collaborative tools that are available to researchers, which ones they use in their work, and what support they feel they need from the University. One of Tamar’s interviewees expressed a view that “[the University’s tools and services] all start with ‘Data-something’, and I need to close my eyes and think which is for what,” a remark which resonated with my own experience upon first starting this job.

When I joined the University’s Library and University Collections as Research Data Support Manager in Summer 2018, I was initially baffled by the seemingly vast range of different data storage and sharing options available to our researchers. By that point I had already worked at Edinburgh for more than a decade, and in my previous role I had little need or obligation to use institutionally-supported services. Consequently, since I rarely if ever dealt with personal or sensitive information, I tended to rely on freely-available commercial solutions: Dropbox, Google Docs, Evernote – that sort of thing. Finding myself now in a position where I and my colleagues were required to advise researchers on the most appropriate systems for safely storing and sharing their (often sensitive) research data, I set about producing a rough aide memoire for myself, briefly detailing the various options available and highlighting the key differences between them. The goal was to provide a quick means or identifying – or ruling out – particular systems for a given purpose. Researchers might ask questions like: is this system intended for live or archived data? Does it support collaboration (increasingly expected within an ever more interconnected and international research ecosystem)? Is it suitable for storing sensitive data in a way that assures research participants or commercial partners that prying eyes won’t be able to access their personal information without authorisation? (A word to the wise: cloud-based services like Dropbox may not be!)


[click the image for higher resolution version]

Upon showing early versions to colleagues, I was pleasantly surprised that they often expressed an interest in getting a copy of the document, and thought that it might have a wider potential audience within the University. In the months since then, this document has gone through several iterations, and I’m grateful to colleagues with specific expertise in the systems that we in the Research Data Service don’t directly support (such as the Wiki and the Microsoft Office suite of applications) for helping me understand some of the finer details. The intention is for this to be a living document, and if there are any inaccuracies in this (or indeed subsequent) versions, or wording that could be made clearer, just let us know and we’ll update it. It’s probably not perfect (yet!), but my hope is that it will provide enough information for researchers, and those who support them, to narrow down potential options and explore these in greater depth than the single-page table format allows.

With Tamar’s internship finishing up this week, it feels like a timely moment to release the first of our series of “Quick Guides” into the world. Others will follow shortly, on topics including Research Data Protection, FAIR Data and Open Research, and we will create a dedicated Guidance page on the Research Data Service website to provide a more permanent home for these and other useful documents. We will continue to listen to our researchers’ needs and strive to keep our provision aligned with them, so that we are always lowering the barriers to uptake and serving our primary purpose: to enable Edinburgh’s research community to do the best possible job, to the highest possible standards, with the least amount of hassle.

And if there are other Guides that you think might be useful, let us know!

Martin Donnelly
Research Data Support Manager
Library and University Collections

Research Data Workshop Series 2019

Over the spring of 2019 the Research Data Service (RDS) is holding a series of workshops with the aim of gathering feedback and requirements from our researchers on a number of important Research Data topics.

Each workshop will consist of a small number of short presentations from researchers and research support staff who have experience of the topic. These will then be followed by guided discussions so that the RDS can gather your input on the tools we currently provide, the gaps in our services, and how you go about addressing the challenges and issues raised in the talks.
The workshops for 2019 are:

Electronic Notebooks 1
14th March at King’s Buildings (Fully Booked)

DataVault
1200-1400, 10th April at 6301 JCMB, King’s Buildings, Map
Booking Link – https://www.events.ed.ac.uk/index.cfm?event=book&scheduleID=34308
The DataVault was developed to offer UoE staff a long-term retention solution for research data collected by research projects that are at the completion stage. Each ‘Vault’ can contain multiple files associated with a research project that will be securely stored for an identified period, such as ten years. It is designed to fill in gaps left by existing research data services such as DataStore (active data storage platform) and DataShare (open access online data repository). The service enables you to comply with funder and University requirements to preserve research data for the long-term, and to confidently store your data for retrieval at a future date. This workshop is intended to gather the views of researchers and support staff in schools to explore the utility of the new service and discuss potential practicalities around its roll-out and long-term sustainability.

Sensitive Data Challenges and Solutions
1200-1430, 16th April in Seminar Room 2, Chancellors Building, Bioquarter, Map
Booking Link – https://www.events.ed.ac.uk/index.cfm?event=book&scheduleID=34321
Researchers face a number of technical, ethical and legal challenges in creating, analysing and managing research data, including pressure to increase transparency and conduct research openly. But for those who have collected or are re-using sensitive or confidential data, these challenges can be particularly taxing. Tools and services can help to alleviate some of the problems of using sensitive data in research. But cloud-based tools are not necessarily trustworthy, and services are not necessarily geared for highly sensitive data. Those that are may not be very user-friendly or efficient for researchers, and often restrict the types of analysis that can be done. Researchers attending this workshop will have the opportunity to hear from experienced researchers on related topics.

Electronic Notebooks 2
1200-1430, 9th May at Training & Skills Room, ECCI, Central Area, Map
Booking Link – https://www.events.ed.ac.uk/index.cfm?event=book&scheduleID=34287
Electronic Notebooks, both computational and lab-based, are gaining ground as productivity tools for researchers and their collaborators. Electronic notebooks can help facilitate reproducibility, longevity and controlled sharing of information. There are many different notebook options available, either commercially or free. Each application has different features and will have different advantages depending on researchers or lab’s requirements. Jupyter Notebook, RSpace, and Benchling are some of the platforms that are used at the University and all will be represented by researchers who use them on a daily basis.

Data, Software, Reproducibility and Open Research
Due to unforeseen circumstances this event has been postponed. We will update with the new event details as soon as they are confirmed.
In this workshop we will examine real-life use cases wherein datasets combine with software and/or notebooks to provide a richer, more reusable and long-lived record of Edinburgh’s research. We will also discuss user needs and wants, capturing requirements for future development of the University’s central research support infrastructure in line with (e.g.) the LERU Roadmap for Open Science, which the Library Research Support team has sought to map its existing and planned provision against, and domain-oriented Open Research strategies within the Colleges.

Kerry Miller
Research Data Support Officer
Library & University Collections

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 are published on MediaHopper.

Other resources

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