Introduction to Data Visualisation and Web Applications Using R
This short course offers academics a thorough grounding in creating publication-ready graphics, interactive web resources, and applications using R. Designed for researchers at any stage of the R learning curve, the course takes you from a freshly collected and cleaned dataset through to polished, readily interpretable outputs. Participants will leave equipped to produce clear, compelling visualisations and build simple interactive applications that bring their data to life, whether for publication, teaching, or public engagement.
| Dates | 14-15 June 2027 |
|---|---|
| Fee | £500 |
| Format | Online |
| Audience | Open to all applicants (prerequisites apply) |
| Organisers | Dr Sarah Watkins, Haotian Tang and Dr Gareth Griffith |
Course profile
This course aims to teach participants how to clearly and effectively communicate research findings. It will familiarise participants with data visualisation tools and techniques used in R for the creation of high-quality, dynamic, clear and reproducible graphics and research reports.
Please click on the sections below for more information:
This online course will be delivered over two consecutive days, with live teaching running from approximately 9:00/9:15am to 4:30pm each day. The course will combine live lectures, practical sessions, breakout group activities and opportunities for questions and discussion. All live lectures will be recorded, and participants are expected to engage actively during practical sessions and discussions to get the most from the course.
By the end of the course participants should be able to:
- articulate the grammar of graphics underpinning ggplot2, and apply this framework to the construction of publication-ready figures;
- evaluate what constitutes an effective data visualisation, and apply principles of visual communication to convey key findings clearly and accurately;
- generate publication-quality figures from cleaned datasets using the ggplot2 package;
- produce interactive graphics suitable for online publication and dissemination using the plotly package; and
- design and deploy interactive web applications using shiny, enabling dynamic exploration and presentation of research data.
The course is intended for individuals with an interest in data visualisation, reproducible research and data science. The course topics apply to nearly all areas of quantitative research, but the course is focussed on visual presentation of data rather than statistical analysis methods.
It is assumed participants will have attended the Introduction to R course or have a similar level of experience with R and/or RStudio. This course is not intended for people who have never used R before.
This course will cover:
1. an introduction to creating plots in R using ggplot2;
2. advanced graphics techniques, including facets, themes, arranging plots and creating interactive plots;
3. the use of examples from published papers to identify plots that present results clearly and intuitively (whether a figure clearly communicates its intended message);
4. using RMarkdown to produce reports, tables and templates; and
5. an introduction to Shiny and further applications for building interactive web applications.
This course is lead by Dr Sarah Watkins, Haotian Tang and Dr Gareth Griffith.
To make sure the course is suitable for you and you will benefit from attending, please ensure you meet the following prerequisites before booking:
| Knowledge | Course participants should either have attended the Introduction to R course or be familiar with R and/or RStudio. This course is not intended for people who have never used R before. |
|---|---|
| Software | This course will use Posit cloud. Participants will not need to install the desktop version of RStudio to complete the course. If course participants would like to use RStudio Desktop (Open Source version) alongside the cloud version, this is compatible with Windows, Mac and Linux and is freely available from: https://rstudio.com/products/rstudio/download/ Go to R Installation Instructions for help getting set up. You will also need software able to open and view .pdf (e.g. Adobe Reader) and .docx files (e.g. MS Word). |
| Recommendation | Participants may find it helpful to have 2 screens. However, this is not a requirement. |
Before booking this course, please make sure you read the information provided above about the target audience and prerequisites. It is important that you have access to the relevant IT resources needed for the course and meet the knowledge prerequisites to ensure you can get the most from the course.
Bookings are taken via our online booking system, for which you must register an account. To check if you are eligible for free or discounted courses please see our fees and voucher packs page. All bookings are subject to our terms and conditions, which can be read in full here.
For help and support with booking a course refer to our booking information page, FAQs or feel free to contact us directly. For available payment options please see: How to pay your short course fees.
Participants are granted access to our virtual learning platform (Blackboard Ultra) 1 to 2 weeks in advance of the course. This allows time for any pre-course work to be completed and to familiarise with the platform.
To gain the most from the course, we recommend that you attend in full and participate in all interactive components. We endeavour to record all live lecture sessions and upload these to the online learning environment within 24 hours. This allows course participants to review these sessions at leisure and revisit them multiple times. Please note that we do not record breakout sessions.
All course participants retain access to the online learning materials and recordings for 5 months after the course.
University of Bristol staff and postgraduate students who do not wish to attend the full course may instead register for access to the 'Materials and Recordings' version of this course: Further information and bookings.
95% of attendees recommend this course*.
*Attendee feedback from 2025.
Here is a sample of feedback from the last run of the course:
"I can't believe I've been a researcher as long as I have without using R Markdown. I always felt that it would be impossible to learn but it was made SO EASY in this course, and I know my science will be better for using it in the future! Even if other elements remain slightly out of reach (looking at you, Shiny), I know this one skill alone will greatly enhance my work.” - Course feedback, February 2025
"This was a very comprehensive course. The course organisers had clearly put a HUGE amount of work into preparing the materials. They provided a lot of useful information about how to produce and customise different graphics, so it was a very useful overview of a lot of material.” - Course feedback, February 2025
"I was also a big fan of having the breakout groups by level - this meant that our group (advanced/intermediate on Day 1 and then moderate on Day 2) could go at our own pace and ask questions as we needed.” - Course feedback, February 2025
"The course ran smoothly and to time, and was very well organised.” - Course feedback, February 2025
"Teaching was excellent. Sarah and Aimee especially have done an absolutely fantastic job! The practicals were the perfect level and all the materials really great. It was helpful to be in small breakout rooms for the purposes of asking questions, but glad we were left to work things through at own pace. I hope tutors didn't feel under-used, they were very appreciated!” - Course feedback, February 2025
"Excellent introduction to ggplot and ggplotly. I liked the breakout sessions as enjoyed being able to work independently at our own pace with a moderator present.” - Course feedback, February 2025
"We did have a lot of opportunities to practise plotting and make sure we really became familiar with the process. The R Markdown was not something I expected, but it seems very useful.” - Course feedback, February 2025
"The lectures and practicals were really useful and well organised. I now feel a lot more confident in using ggplot2 and RMarkdown. Also I think it's helpful that we get to choose which level of breakout room we want to go.” - Course feedback, February 2025
"The course tutors were knowledgeable with engaging materials and very useful resources to support future learning.” - Course feedback, February 2025
"Practical sessions, measured content suitable for the allotted time, good time management, knowledgeable tutors and moderators.” - Course feedback, February 2025
"The schedule for the day was good - and a blend of breakout rooms with more localised help really benefitted the learning experience.” - Course feedback, February 2025