- Overview
- Instructors
- Schedule
Course Description
This FREE 4 hour course is delivered by Dr Martijn Tenneckes, author of the tmap package. tmap is one of the most widely used packages for spatial data visualization. The course begins with an overview of the core R packages for spatial data analysis and visualisation, providing participants with a solid foundation in the tools most commonly used for mapping and spatial workflows. Building on this, we explore how to create common thematic map types using the powerful tmap package, followed by a practical session on designing effective and visually engaging colour palettes with cols4all. We then conclude with a discussion of the underlying methodology of spatial data visualisation, ensuring that participants not only know how to make maps in R, but also understand the principles behind effective and meaningful spatial representation.
This course is part of a longer, paid for course, details of which can be found hereSpatial Data Visualisation and Mapping using TMAP.
What You’ll Learn
During the course will cover the following:
- Understand the core R packages available for spatial data analysis and visualisation.
- Create common thematic map types using the tmap package in R.
- Apply effective colour palettes for spatial visualisation using cols4all.
- Explain key principles and methodologies underpinning spatial data visualisation.
Course Format
Interactive Learning Format
Each day features a well-balanced combination of lectures and hands-on practical exercises, with dedicated time for discussing participants’ own data, time permitting.
Global Accessibility
All live sessions are recorded and made available on the same day, ensuring accessibility for participants across different time zones.
Collaborative Discussions
Open discussion sessions provide an opportunity for participants to explore specific research questions and engage with instructors and peers.
Comprehensive Course Materials
All code, datasets, and presentation slides used during the course will be shared with participants by the instructor.
Personalized Data Engagement
Participants are encouraged to bring their own data for discussion and practical application during the course.
Post-Course Support
Participants will receive continued support via email for 30 days following the course, along with on-demand access to session recordings for the same period.
Who Should Attend / Intended Audiences
This course is intended for anyone, but in particular academics and postgraduate students working on spatial data projects, as well as applied researchers and analysts in the public, private, or third sectors who require the reproducibility, speed, and flexibility of a command-line language like R for spatial data analysis and visualisation. It is also well-suited for data journalists aiming to produce engaging and informative maps for news stories, dashboards, and infographics, and for current R users seeking to update their skills with spatial data packages, particularly tmap. Participants should have a basic understanding of mathematical and statistical concepts and be comfortable using R, including tasks such as importing and exporting data, manipulating data frames, and creating simple exploratory plots. Of course if you don’t have any of these you are still welcome to join and listen and revisit the material from the recordings we provide.
Equipment and Software requirements
A laptop or desktop computer with a functioning installation of R and RStudio is required. Both R and RStudio are free, open-source programs compatible with Windows, macOS, and Linux systems.
A working webcam is recommended to support interactive elements of the course. We encourage participants to keep their cameras on during live Zoom sessions to foster a more engaging and collaborative environment.
While not essential, using a large monitor—or ideally a dual-monitor setup—can significantly enhance your learning experience by allowing you to view course materials and work in R simultaneously.
All necessary R packages will be introduced and installed during the workshop. A comprehensive list of required packages will also be shared with participants ahead of the course to allow for optional pre-installation.
Dr. Martijn Tennekes
Martijn is a statistician and data scientist with two decades of experience in teaching, academic research, and applied consulting. He specialises in data visualisation, spatial data analysis, and statistical programming, with a strong focus on open-source tools and reproducible research. An R enthusiast, Martijn is the main author of several widely used R packages for data analysis and mapping.
His career spans collaborations with numerous academic institutions, including Eindhoven University of Technology and the University of Oxford, and he has led multiple training courses for the European Commission (Eurostat). Martijn is currently based at Statistics Netherlands, where he works in the methodology department contributing to international research and innovation in statistical methods.
Martijn holds a PhD in game theory from Maastricht University (2010) and has since applied his theoretical background to practical challenges in data science and spatial analytics.
Education & Career
• 20 years of experience in statistical consulting, academic research, and teaching
• PhD in Game Theory, Maastricht University (2010)
• Senior Methodologist at Statistics Netherlands
• Course leader for Eurostat (European Union) training programs
• Collaborator with universities (including Eindhoven and Oxford) and intergovernmental organisations.
Research Focus
Martijn’s work focuses on the development and application of statistical programming techniques for data visualisation and spatial data analysis. He is particularly interested in leveraging R for creating reproducible, insightful data products and visual tools that support decision-making in research and policy.
Current Projects
• Development of R packages for spatial and statistical visualisation
• Applied research in statistical methodology at Statistics Netherlands
• Training on statistical computing and spatial data analysis with R across Europe
Teaching & Skills
• Expert in R programming, spatial analysis, and statistical visualisation
• Experienced in teaching R for applied data science, mapping, and modelling
• Active contributor to the R community and open-source development
Links
• GitHub
• TMAP
• LinkedIn
• ResearchGate
Session 1 – 01:00:00 – Overview of the core R packages for spatial data analysis and visualisation.
Session 2 – 01:00:00 – Creating Common Thematic Map Types Using the R Package tmap
Break – 01:00:00
Session 3 – 01:00:00 – Exploring Colour Palettes with the R Package cols4all
Session 4 – 01:00:00 – Methodology of Spatial Data Visualisation
Frequently asked questions
Everything you need to know about the product and billing.
When will I receive instructions on how to join?
You’ll receive an email on the Friday before the course begins, with full instructions on how to join via Zoom. Please ensure you have Zoom installed in advance.
Do I need administrator rights on my computer?
I’m attending the course live — will I also get access to the session recordings?
I can’t attend every live session — can I join some sessions live and catch up on others later?
I’m in a different time zone and plan to follow the course via recordings. When will these be available?
I can’t attend live — how can I ask questions?
Will I receive a certificate?
When will I receive instructions on how to join?
You’ll receive an email on the Friday before the course begins, with full instructions on how to join via Zoom. Please ensure you have Zoom installed in advance.
Do I need administrator rights on my computer?
I’m attending the course live — will I also get access to the session recordings?
I can’t attend every live session — can I join some sessions live and catch up on others later?
I’m in a different time zone and plan to follow the course via recordings. When will these be available?
I can’t attend live — how can I ask questions?
Will I receive a certificate?
Still have questions?
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