University of Edinburgh, King's Buildings, JCMB

May 11-12, 2017

9:00 - 17:00

Instructors: Eilidh Troup, Giacomo Peru, Manos Farsarakis, Mike Jackson

Helpers: Adam Carter, Alexey Tarutin, Mario Antonioletti, Neelofer Banglawala

General Information

Data Carpentry workshops are for any researcher who has data they want to analyze, and no prior computational experience is required. This hands-on workshop teaches basic concepts, skills and tools for working more effectively with data.

This workshop is hosted by EPCC, Edinburgh Parallel Computing Centre, and organised in collaboration by ARCHER, the Software Sustainability Institute, and UoE Research Data Service.

ARCHER, the UK's national supercomputing service, offers training in software development and high-performance computing to scientists and researchers across the UK. As part of our training service we are running a two-day Data Carpentry workshop.

The Software Sustanability Institute's mission is to cultivate better, more sustainable, research software to enable world-class research (better software, better research). Software is fundamental to research: seven out of ten UK researchers report that their work would be impossible without it.

The Research Data Service is a suite of tools and support for University staff and students to aid them in data management planning, working with data, sharing and preserving their data, and re-skilling. It is delivered by a virtual team spanning across a number of sections of Information Services including EDINA and Data Library, Library & University Collections, IT Infrastructure, User Services, and the Digital Curation Centre.

We will cover Data organization in spreadsheets and OpenRefine, Introduction to R, Data analysis and visualization in R and SQL for data management. Participants should bring their laptops and plan to participate actively. By the end of the workshop learners should be able to more effectively manage and analyze data and be able to apply the tools and approaches directly to their ongoing research.

Who: The course is aimed at graduate students and other researchers.

Where: Room 3217, James Clerk Maxwell Building, Peter Guthrie Tait Road, Edinburgh, EH9 3FD. Get directions with OpenStreetMap or Google Maps.

Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating sytem (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed (listed below). They are also required to abide by Data Carpentry's Code of Conduct.

Contact: Please mail; for more information.


To register, or to get more information, please, visit the ARCHER training page.


Please be sure to complete these surveys before and after the workshop.

Pre-workshop Survey

Post-workshop Survey


Day 1

09:00 Welcome and setup
09:30 Caveats of working with data in spreadsheets
10:00 Introduction to Open Refine
10:30 Coffee break
11:00 Working with Open Refine
12:30 Lunch break
13:30 Introduction to data manipulation with R - part 1
15:00 Coffee break
15:30 Introduction to data manipulation with R - part 2
17:00 Close

Day 2

09:00 Data visualisation with R - part 1
10:30 Coffee break
11:00 Data visualisation with R - part 2
12:30 Lunch break
13:30 Introduction to data manipulation with SQL - part 1
15:00 Coffee break
15:30 Introduction to data manipluation with SQL - part 2
16:30 Wrap-up and feedback
17:00 Close

We will use this Etherpad for chatting, taking notes, and sharing URLs and bits of code.



To participate in a Data Carpentry workshop, you will need working copies of the described software. Please make sure to install everything (or at least to download the installers) before the start of your workshop. Participants should bring and use their own laptops to insure the proper setup of tools for an efficient workflow once you leave the workshop.

Please follow these Setup Instructions.

We maintain a list of common issues that occur during installation as a reference for instructors that may be useful on the Configuration Problems and Solutions wiki page.