Minor Geospatial Data Science

Academic year 2025-2026, semester 1a and 1b

Offered by: Faculty of Spatial Sciences
ECTS: 30
Coordinator: dr.ir. S.G. Weitkamp
Maximum number of applications: 35

Introduction

Explore the world through data! Spatial information is crucial for understanding and addressing major societal challenges. From predicting climate change impacts to unraveling the spatial inequalities of wellbeing, these complex issues benefit from a multidisciplinary approach. By combining spatial and computational thinking, we can use the power of spatial data to find sustainable solutions.

The University of Groningen is excited to offer a cutting-edge minor in Geospatial Data Science. This interdisciplinary program is designed to equip you with the skills to analyze and interpret spatial data using advanced computational tools to tackle important global societal challenges.

Why choose this minor?

Real-world impact: Work on a challenge-based project that addresses real societal issues in the Northern Netherlands, such as sustainable urban planning, renewable energy distribution, and social inequalities in mobility.
Interdisciplinary learning: Bridging your own discipline with spatial science, computer science, and statistics, this program offers you a unique blend of knowledge and skills, preparing you for a career in a wide range of professions.
Practical skills: Gain hands-on experience in spatial data analysis, visualization, and the application of programming skills to a variation of big spatial datasets.

Programme structure

ECTS Credits: 30 EC
Semester 1a and 1b
Language of Instruction: English
Participation Limit: Maximum 35 students

In Semester 1a, during the first week of the minor, you write a starting document describing your personal learning objectives as part of an introductory course on Geospatial Data Science. Additionally, you select two skills courses of a combined 10 ECTS from a range of options. In Semester 1b, you learn all about data visualization, and you apply your spatial and computational skills, along with your disciplinary knowledge, to a collaborative real-world challenge-based project. See below for the more detailed programme. From 1 July you can view updates and more details in Ocasys and the schedule of the courses on rooster.rug.nl.

Course code ECTS Semester Compulsory or Elective	Course name	Short description
GEIGSDS (5 ECTS) Semester 1a, Compulsory	Introduction to Geospatial Data Science	Welcome to the introductory course on Geospatial Data Science (GDS), where we delve into the dynamic intersection of geography and data science. This course spans seven engaging lectures, designed to provide students with a solid foundation in geospatial data science. You'll gain valuable knowledge and insights into its relevance and applications across diverse disciplines.
GEASDA (5 ECTS) Semester 1a, Elective	Advanced Spatial Data Analysis	In this course students further develop their spatial and computational thinking skills and learn to apply these with the use of new geospatial technologies to address spatial problems. More specifically, in this course you will learn the basics of programming in python, integrating python with QGIS, and how you can effectively use these in relation to spatial problems.
LPX065B05 (5 ECTS) Semester 1a, Elective	Introduction to GIS	Almost all kinds of data can be linked to a location in one way or another, even though the conceptual difference between space and place has methodological implications. What contributions can spatial technologies such as Geographic Information Systems (GIS) make to spatial science? What are the challenges at stake? What are the new trends? During this module, students learn how GIS help address a variety of questions, and they are acquainted with the use of geographical and spatial data as a source for research and management within the different subfields of Spatial Science.
GEMLGS (5 ECTS) Semester 1a, Elective	Machine Learning in Geospatial Data Science	The course introduces the fundamental concepts and techniques of machine learning (ML) within the context of geospatial data science. You will learn how to apply basic ML algorithms using Python to analyse and interpret geospatial datasets. Key topics include data preprocessing, regression, classification, clustering, and dimensionality reduction. The course emphasizes practical skills through hands-on exercises, integrating Geographic Information Systems (GIS) tools with machine learning workflows.
UCGMIN01 (5 ECTS) Semester 1a, Elective	Programming in Phyton	As the computers have become prevalent both in academia and industry, it is important for the professionals to have “computational thinking” as a core competency. The students across many disciplines can greatly benefit from understanding the underlying principles of computing and gaining basic programming skills. This course introduces the fundamentals of programming including data types, control structures, algorithm development, functions and designing/implementing/debugging simple programs via the Python programming language.
CFBDS04A05 (5 ECTS) Semester 1b, Compulsory	Visualising Data	As data continues to grow in both availability and complexity, there is a rising demand for professionals skilled in data communication. Data visualization plays a pivotal role in meeting this need. For data analysts, scientists, or business professionals, the ability to craft compelling visualizations is essential for effective data communication. This course offers an introduction to the principles and techniques of data visualization, a crucial element of effective data communication. Various methods and tools for creating impactful visualizations of complex data sets will be explored. Topics will include data cleaning, chart design, digital tools, programming libraries, digital platforms, and storytelling through data.
GEIAGSC (10 ECTS) Semester 1b, Compulsory	Interdisciplinary Approaches to Geospatial Challenges	This course provides students with the opportunity to apply their geospatial data analysis skills in a practical, challenge based setting. Students will work in groups on a research / analysis project in collaboration with an external client.

Learning experience

Foundation: Build your knowledge base with an introductory course in geospatial data science.
Skill Courses: Choose two electives from courses like GIS basics, programming in python, machine learning with geodata, and data visualization to enhance your technical skills. You work mostly in small groups on collaborative assignments.
Challenge based Project: Apply your skills and the knowledge from your own discipline in a comprehensive interdisciplinary project that involves real-world problems, provided by local organizations in the Northern Netherlands. You work in a group of maximum five students.

Course registration

To register for the minor in Progress, navigate to the first menu item labeled "Minors" and select "Spatial Sciences". For detailed information on registration deadlines and additional requirements, please visit the Minor website. For the academic year 2025-2026, registration opens on May 23, 2025, at 0:00 PM (midnight) and closes on July 4, 2025, at 23:59 PM.

You must register for the course units separately at the Faculty of Spatial Sciences - Minor Geospatial Data Science in the Progress Portal. The course registration for semester 1a opens on 16 June and closes on 30 August 23.59 pm. The course registration for semester 1b opens on 15 September and closes on 12 October, 23.59 pm.

Admissions

Open to: All third year bachelor students of the University of Groningen.
Recommended background: To make the most of this minor, candidates are strongly advised to have the following competencies before enrollment:
A solid understanding of basic statistical concepts and techniques, such as those learned in course CFBDS07A05 or GESTAT1, and the ability to apply basic statistical methods to analyze and interpret data.
Either basic skills in handling spatial data (e.g. using GIS software) OR basic programming skills (e.g. python, R, or comparable programming language)

Preparation

Once you have been registered for the program, you are required to fill in a survey before the start of the minor. In this survey, you outline your motivation for joining the program and include your existing skills in spatial analysis or computation, and statistics. Additionally, you specify your personal learning objectives in alignment with the program's learning outcomes. You also indicate which skills courses you are interested in enrolling in and the themes for a challenge-based project that interest you. Submitting this survey on time will ensure a smooth and efficient start to the minor program. More detailed information will be provided after you have been admitted to the minor programme.

You are expected to bring a laptop that you will use during computer practical sessions.

Contact

Contact
For more information, contact the minor coordinator, Gerd Weitkamp: s.g.weitkamp@rug.nl.

Testimonials

This project and minor have brought out more in me than I initially expected, pushing me to develop in ways I hadn't realized before. As our coordinators often emphasized, we continuously improved throughout the time we worked on this project. The combination of skill courses in the first block and the hands-on experience of planning, debating, and building the project with our client and team required each of us to adapt, grow, and refine our abilities. The interdisciplinary nature of the project challenged us to think critically and collaborate effectively while benefiting from the guidance of experienced professionals who were always available to support us. I would highly recommend this minor to anyone looking for an opportunity to work on a complex, multifaceted project while receiving valuable mentorship and gaining practical experience.

- Ana Ciortescu

From the beginning I was able to shape my own learning experience by selecting electives and topics for projects that aligned with my interests. In addition to the electives, I learned valuable insights during weekly guest lectures into the broad applicability of geospatial data science across domains extending from healthcare to business. The second half of the minor featured an extensive hands-on project that really encouraged critical thinking and creativity. Working in multidisciplinary teams as well as in collaboration with a client, provided a new intake on group work and closely resembled real-world collaborative projects, particularly in my case, in the field of spatial planning. I am really happy with the structure and the environment this minor had to offer. It was challenging and rewarding at the same time filled with highly-skilled professors eager to help and motivated peers. During this time, I advanced my GIS skills, started programming, touched some machine learning concepts and most importantly, solidified my passion for geospatial data science.

- Austeja Tarvydaite

This minor provided me with the opportunity to broaden my skill-set and gave me new insights into the world of geospatial data science. With my background in Spatial Planning and Design, I was already familiar with ArcGIS, this minor gave me the opportunity to also explore Python and QGIS through my skill courses and the final project. Working with a client was an intriguing learning experience. A personal highlight was a brainstorming session we had with people from different departments from our client. Furthermore, working in a group on such a project requires the development of a lot of soft skills; presenting, effective communication and fostering a productive work atmosphere. Throughout the whole minor there was a focus on everyone’s learning process. Within this open atmosphere everybody got the chance to flourish and grow. Furthermore this minor gave me a new perspective on geospatial data science as a possible career and also for choosing electives during my master.

- Ruben Haadsma

Victor's experience with the minor Geospatial Data Science

When it came time to choose a minor, I knew I wanted something that would push my boundaries even further.

Hey! I'm Victor Toma, and I come from Romania. I'm currently in my third and final year of studying Data Science & Society. My journey through this programme has been nothing short of eye-opening, and when it came time to choose a minor, I knew I wanted something that would push my boundaries even further. That’s why I chose Geospatial Data Science. I thought it would not only complement my studies but also introduce me to a different niche within the vast field of data science.......

Read more about Victor's experience with the minor Geospatial Data Science in this blog!

Last modified:

01 May 2025 1.01 p.m.