Designing and curating a data analysis workflow is a fundamental element of research processes. Effective workflow design can ensure that research goals and data are connected through appropriate methodology for reliable interpretations and research outputs.
Across disciplines, domain conventions for data analysis methodologies from applied statistics to qualitative investigations may differ and vary. In the absence of congruence and standardisation for analyses, researchers must approach their data analysis workflows from goal conception, and data curation to results with a set of guiding frameworks. This short course aims to outline a series of steps to guide the design of an effective data analysis workflow and to enable you to build a domain centred toolkit that can be adapted for many use cases.
Authors for this course: Dr. Somya Iqbal ([email protected])
What to expect at the session 02/02/2026
- Practical hands-on exercises
- Group work
- Talks from tutor
- Q & A session
Course structure (3 hours) 14:00-17:00
- Each hour will be broken into a 15-20 minute talk and 35-40 minutes of working through hands-on exercises & paired work to apply conceptual principles to data analysis workflows. Break will be incorporated at 15:30.
It is helpful to have a project in mind (research project with data collected or to be collected) that you aim to start or have started for discussion and feedback.
The session will include 3 practical elements with linked talks to guide you. No prior experience is required, all steps will be supported by the tutor.
- We will work with Miro and invites will be sent to you for the board on the day of the course.
- We will work with a platform (free) called KNIME - this must be installed on your PC ahead of the session (instructions below).
- Noteable and jupyter notebook using python code.
Further information will be provided on the day
If you are part of the University of Edinburgh you can use Noteable the cloud-based computational notebook system which works on your browser from any device.
- Open the following link in a new tab: https://noteable.edina.ac.uk/login
- Login with your EASE credentials
- Under 'Standard Python 3 Notebook' click 'Start'
- From the Noteable home page, click on the 'Git'>'Clone a Repository' button at the top bar of the screen and enter the link of this repo https://github.com/DCS-training/Data-Analysis-Workflow-Design.git
- You now have imported the full repo and you can see all the material required in the python folder.
- Double-click on the python folder.
- Further instructions to be followed on the day.
KNIME is a free open source software for data analysis and has a user-friendly interface. Guidance will be provided for this practical on the day.
- Download KNIME Download KNIME Analytics Platform | KNIME
- If you are a student or do not have administrative access to install the software please follow the guidance for short term admin rights to install the tool by requesting the 'make me admin' app in the software library of your managed laptop. Permissions from UofE: Make Me Admin | Computing | Information Services
- Once you are able to download the installer, follow default instructions as prompted from KNIME.
- Files for the KNIME exercise will be provided on this repository.
Miro is an online workspace for collaborative engagement.
The University provides access to Miro for staff & students. An invite will be sent to your email to join the board for this session (support available on the day).
This repository has a 