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

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.

[youtube]https://youtu.be/ycCiXoJw1MY[/youtube]

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

Scoping Statistical Analysis Support

The following is a post by our former PhD Intern, Cindy Nelson-Viljoen, where she outlines her experience of working on a significant Data Library project supported by the Innovation Fund.

Scoping Statistical Analysis Support, supported by the Information Services Innovation Fund and managed by Diarmuid McDonnell, was a six-month project that aimed to identify gaps in statistical analysis training provision at the University of Edinburgh, and the potential role of the Data Library in addressing these gaps. The focus was on understanding how statistical analysis support and training is conducted across University of Edinburgh schools; scoping existing support mechanisms and models for students, researchers and teachers; and identifying services and support that would satisfy existing or future demand.

The activities of the project included designing an online questionnaire of research students, and to engage with and interview faculty (researchers and teachers) with knowledge of and responsibility for quantitative methods/statistical analysis support in their respective school. As part of the project, the Data Library employed a PhD intern (Cindy Nelson-Viljoen) via the Employ.ed scheme, and offered an excellent opportunity for Cindy to develop her knowledge of social science methods, statistical analysis and support, and research data management in a collaborative cross-disciplinary setting.

The project’s findings will inform future planning of statistical analysis support and training within the Data Library, ISG and the University. The report describing the project, methodology, findings and recommendations is available at http://edin.ac/2hnJYPb.

MANTRA @ Melbourne

The aim of the Melbourne_MANTRA project was to review, adapt and pilot an online training program in research data management (RDM) for graduate researchers at the University of Melbourne. Based on the UK-developed and acclaimed MANTRA program, the project reviewed current UK content and assessed its suitability for the Australian and Melbourne research context. The project team adapted the original MANTRA modules and incorporated new content as required, in order to develop the refreshed Melbourne_MANTRA local version. Local expert reviewers ensured the localised content met institutional and funder requirements. Graduate researchers were recruited to complete the training program and contribute to the detailed evaluation of the content and associated resources.

The project delivered eight revised training modules, which were evaluated as part of the pilot via eight online surveys (one for each module) plus a final, summative evaluation survey. Overall, the Melbourne_MANTRA pilot training program was well received by participants. The content of the training modules generally gathered high scores, with low scores markedly sparse across all eight modules. The participants recognised that the content of the training program should be tailored to the institutional context, as opposed to providing general information and theory around the training topics. In its current form, the content of the modules only partly satisfies the requirements of our evaluators, who made valuable recommendations for further improving the training program.

In 2016, the University of Melbourne will revisit MANTRA with a view to implement evaluation feedback into the program; update the modules with new content, audiovisual materials and exercises; augment targeted delivery via the University’s LMS; and work towards incorporating Melbourne_MANTRA in induction and/or reference materials for new and current postgraduates and early career researchers.

The current version is available at: http://library.unimelb.edu.au/digitalscholarship/training_and_outreach/mantra2

Dr Leo Konstantelos
Manager, Digital Scholarship
Research | Research & Collections
Academic Services
University of Melbourne
Melbourne, Australia