Research Data Training: Semester Two, 2020/21

As we are still facing significant restrictions on movement and in-person events during the whole of semester 2 we have decided to continue offering our RDM (Research Data Management) training courses online only. Details of the upcoming courses are below.

For undergraduate and taught masters students we have a new course called Data Mindfulness: Making the most of your dissertation, which can be enroled on via Learn on MyEd. Alternatively the videos and workbook are available on our training page.

Our online, self-paced RDM training course, Research Data MANTRA, has also been undergoing a significant update, which will be the subject of a future blog post – it is openly accessible at https://mantra.edina.ac.uk.

Full details about each course are on our training webpage https://www.ed.ac.uk/information-services/research-support/research-data-service/training

Workshop Audience Date Time Booking Link
Writing A Data Management Plan for Your Research (RDS002) Research Staff 24th March 2021 09:30 – 11:30 https://www.events.ed.ac.uk/index.cfm?event=book&scheduleId=44117
Writing A Data Management Plan for Your Research (RDS002) All Staff & PGR’s 13th April 2021 10:00 – 12:00 https://www.events.ed.ac.uk/index.cfm?event=book&scheduleID=44862
Working with Personal and Sensitive Data (RDS003) Research Staff 15th April 2021 09:30 – 11:30 https://www.events.ed.ac.uk/index.cfm?event=book&scheduleId=44118
Realising the Benefits of Good Research Data Management (RDS001) All Staff & PGR’s 21 & 22 April 2021 13:30 – 15:00 Part 1 – https://www.events.ed.ac.uk/index.cfm?event=book&scheduleID=44856

Part 2 – ttps://www.events.ed.ac.uk/index.cfm?event=book&scheduleID=44861

Edinburgh DataVault: supporting users archiving their research data (RDS008) Support staff 22nd April 2021 10:30 – 12:00 https://www.events.ed.ac.uk/index.cfm?event=showEventDetails&scheduleId=44924
Working with Personal and Sensitive Data (RDS003) All Staff & PGR’s 26th April 2021 14:00 – 16:00 https://www.events.ed.ac.uk/index.cfm?event=book&scheduleID=44863
Realising the Benefits of Good Research Data Management (RDS001) Research Staff 04 & 05 May 2021 13:30 – 15:00 Contact IAD directly https://www.ed.ac.uk/institute-academic-development

The following courses will not run during semester 2, but we plan to relaunch them as soon possible. In the meantime if you need any support just get in touch with us via data-support@ed.ac.uk and we’ll be happy to help.

  • Data Cleaning with OpenRefine (RDS004)
  • Handling Data Using SPSS (RDS005)
  • Assessing Disclosure Risk in Quantitative Data (RDS006)
  • Assessing Data Quality in Quantitative Data (RDS007)
  • Introduction to Visualising Data in ArcGIS (RDS011)
  • Introduction to Visualising Data in QGIS (RDS012)

A final note, the Research Data Management and Sharing MOOC which we launched with the University of North Carolina in 2016 has enjoyed its most successful period during the pandemic, with people wanting to reskill for the digital world. Over 2,700 learners have successfully completed the 5 week course and passed assessments, with over 25,000 people engaging with the highly rated course since the beginning.

Kerry Miller
Research Data Support Officer
Library and University Collections

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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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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

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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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