Data Carpentry & Software Carpentry workshops

The Research Data Service hosted back to back 2-day workshops in the Main Library this week, run by the Software Sustainability Institute (SSI) to train University of Edinburgh researchers in basic data science and research computing skills.

Learners at Data Carpentry workshop

Learners at Data Carpentry workshop

Software Carpentry (SC) is a popular global initiative originating in the US, aimed at training researchers in good practice in writing, storing and sharing code. Both SC and its newer offshoot, Data Carpentry, teaches methods and tools that helps researchers makes their science reproducible. The SSI, based at Edinburgh Parallel Computing Centre (EPCC), organises workshops for both throughout the UK.

Martin Callaghan, University of Leeds

Martin Callaghan, University of Leeds, introduces goals of Data Carpentry workshop.

Each workshop is taught by trainers trained by the SC organisation, using proven methods of delivery, to learners using their own laptops, and with plenty of support by knowledgeable helpers. Instructors at our workshops were from Leeds and EPCC. Comments from the learners – staff and postgraduate students from a range of schools, included, ‘Variety of needs and academic activities/disciplines catered for. Useful exercies and explanations,’ and ‘Very powerful tools.’

Lessons can vary between different workshops, depending on the level of the learners and their requirements, as determined by a pre-workshop survey. The Data Carpentry workshop on Monday and Tuesday included:

  • Using spreadsheets effectively
  • OpenRefine
  • Introduction to R
  • R and visualisation
  • Databases and SQL
  • Using R with SQLite
  • Managing Research & Data Management Plans

The Software Carpentry workshop was aimed at researchers who write their own code, and covered the following topics:

  • Introduction to the Shell
  • Version Control
  • Introduction to Python
  • Using the Shell (scripts)
  • Version Control (with Github)
  • Open Science and Open Research
Software Carpentry learners

Software Carpentry learners

Clearly the workshops were valued by learners and very worthwhile. The team will consider how it can offer similar workshops in the future at a similarly low cost; your ideas welcome!

Robin Rice
EDINA and Data Library


New MOOC! Research Data Management and Sharing

[Guest post from Dr. Helen Tibbo, University of North Carolina-Chapel Hill]

The School of Information and Library Science and the Odum Institute at the University of North Carolina-Chapel Hill and EDINA at the University of Edinburgh are pleased to announce the forthcoming Coursera MOOC (Massive Open Online Course), Research Data Management and Sharing.

CaptureThis is a collaboration of the UNC-CH CRADLE team (Curating Research Assets and Data Using Lifecycle Education) and MANTRA. CRADLE has been funded in part by the Institute of Museum and Library Services to develop training for both researchers and library professionals. MANTRA was designed as a prime resource for postgraduate training in research data management skills and is used by learners worldwide.

The MOOC uses the Coursera on-demand format to provide short, video-based lessons and assessments across a five-week period, but learners can proceed at their own pace. Although no formal credit is assigned for the MOOC, Statements of Accomplishment will be available to any learner who completes a course for a small fee.

The Research Data Management and Sharing MOOC will launch 1st March, 2016, and enrolment is open now. Subjects covered in the 5-week course follow the stages of any research project. They are:

  • Understanding Research Data
  • Data Management Planning
  • Working with Data
  • Sharing Data
  • Archiving Data

Dr. Helen Tibbo from the School of Information and Library Science (SILS) at the University of North Carolina at Chapel Hill delivers four of the five sets of lessons, and Sarah Jones, Digital Curation Centre, delivers the University of Edinburgh-developed content in Week 3 (Working with Data). Quizzes and supplementary videos add to the learning experience, and assignments are peer reviewed by fellow learners, with questions and answers handled by peers and team teachers in the forum.

Staff from both organizations will monitor the learning forums and the peer-reviewed assignments to make sure learners are on the right track, and to watch for adjustments needed in course content.

The course is open to enrolment now, and will ‘go live’ on 1st March.

Hashtag: #RDMSmooc

A preview of one of the supplementary videos is now available on Youtube:

Please join us in this data adventure.

Dr. Helen R. Tibbo, Alumni Distinguished Professor
President, 2010-2011 & Fellow, Society of American Archivists
School of Information and Library Science
201 Manning Hall, CB#3360
University of North Carolina at Chapel Hill
Chapel Hill, NC 27599-3360
Tel: 919-962-8063
Fax: 919-962-8071


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:

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


Fostering open science in social science

FOSTER_logoOn 10th of June, the Data Library team ran two workshops in association with the EU Horizon 2020 project, FOSTER (Facilitate Open Science Training for European Research), and the Scottish Graduate School of Social Science.

The aim of the morning workshop, “Good practice in data management & data sharing with social research,” was to provide new entrants into the Scottish Graduate School of Social Science with a grounding in research data management using our online interactive training resource MANTRA, which covers good practice in data management and issues associated with data sharing.

The morning started with a brief presentation by Robin Rice on ‘open science’ and its meaning for the social sciences. Pauline Ward then demonstrated the importance of data management plans to ensure work is safeguarded and that data sharing is made possible. I introduced MANTRA briefly, and then Laine Ruus assigned different MANTRA units to participants and asked them to briefly go through the units and extract one or two key messages and report back to the rest of the group. After the coffee break we had another presentation on ethics, informed consent and the barriers for sharing, and we finished the morning session with a ‘Do’s and Dont’s exercise where we asked participants to write in post-it notes the things they remembered, the things they were taking with them from the workshop: green for things they should DO, and pink for those they should NOT. Here are some of the points the learners posted:

– consider your usernames & passwords
– read the Data Protection Act
– check funder/institution regulations/policies
– obtain informed consent
– design a clear consent form
– give participants info about the research
– inform participants of how we will manage data
– confidentiality
– label your data with enough info to retrieve it in future
– develop a data management plan
– follow the certain policies when you re-use dataset[s] created by others
– have a clear data storage plan
– think about how & how long you will store your data
– store data in at least 3 places, in at least 2 separate locations
– backup!
– consider how/where you back up your data
– delete or archive old versions
– data preservation
– keep your data safe and secure with the help of facilities of fund bodies or university
– think about sharing
– consider sharing at all stages. Think about who will use my data next
– share data (responsibly)

– unclear informed consent
– a sense of forcing participants to be part of research
– do not store sensitive information unless necessary
– don’t staple consent forms to de-identified data records/store them together
– take information security for granted
– assume all software will be able to handle your data
– don’t assume you will remember stuff. Document your data
– assume people understand
– disclose participants’ identity
– leave computer on
– share confidential data
– leave your laptop on the bus!
– leave your laptop on the train!
– leave your files on a train!
– don’t forget it is not just my data, it is public data
– forget to future proof

Robin Rice presenting at FOSTERing Open Science workshop

Our message was that open science will thrive when researchers:

  • organise and version their data files effectively,
  • provide comprehensive and sufficient documentation for others to understand and replicate results and thus cite the source properly
  • know how to store and transport your data safely and securely (ensuring backup and encryption)
  • understand legal and ethical requirements for managing data about human subjects
  • Recognise the importance of good research data management practice in your own context

The afternoon workshop on “Overcoming obstacles to sharing data about human subjects” built on one of the main themes introduced in the morning, with a large overlap of attendees. The ethical and regulatory issues in this area can appear daunting. However, data created from research with human subjects are valuable, and therefore are worth sharing for all the same reasons as other research data (impact, transparency, validation etc). So it was heartening to find ourselves working with a group of mostly new PhD students, keen to find ways to anonymise, aggregate, or otherwise transform their data appropriately to allow sharing.

Robin Rice introduced the Data Protection Act, as it relates to research with human subjects, and ethical considerations. Naturally, we directed our participants to MANTRA, which has detailed information on the ethical and practical issues, with specific modules on “Data protection, rights & access” and “Sharing, preservation & licensing”. Of course not all data are suitable for sharing, and there are risks to be considered.

In many cases, data can be anonymised effectively, to allow the data to be shared. Richard Welpton from the UK Data Archive shared practical information on anonymisation approaches and tools for ‘statistical disclosure control’, recommending sdcMicroGUI (a graphical interface for carrying out anonymisation techniques, which is an R package, but should require no knowledge of the R language).

DrNiamhMooreFinally Dr Niamh Moore from University of Edinburgh shared her experiences of sharing qualitative data. She spoke about the need to respect the wishes of subjects, her research gathering oral history, and the enthusiasm of many of her human subjects to be named in her research outputs, in a sense to own their own story, their own words.


Rocio von Jungenfeld & Pauline Ward
EDINA and Data Library