290700 VU Geo-Data and Geo-Data Management (2026S)
Continuous assessment of course work
Labels
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Mo 09.02.2026 08:00 to Mo 23.02.2026 08:00
- Deregistration possible until Tu 31.03.2026 23:59
Details
max. 30 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
- Thursday 05.03. 12:30 - 15:30 Multimedia Mapping-Labor, NIG 1.Stock C0110
- Thursday 19.03. 12:30 - 15:30 Multimedia Mapping-Labor, NIG 1.Stock C0110
- Thursday 26.03. 12:30 - 15:30 Multimedia Mapping-Labor, NIG 1.Stock C0110
- Thursday 16.04. 12:30 - 15:30 Multimedia Mapping-Labor, NIG 1.Stock C0110
- Thursday 23.04. 12:30 - 15:30 Multimedia Mapping-Labor, NIG 1.Stock C0110
- Thursday 30.04. 12:30 - 15:30 Multimedia Mapping-Labor, NIG 1.Stock C0110
- Thursday 07.05. 12:30 - 15:30 Multimedia Mapping-Labor, NIG 1.Stock C0110
- Thursday 21.05. 12:30 - 15:30 Multimedia Mapping-Labor, NIG 1.Stock C0110
- Thursday 28.05. 12:30 - 15:30 Multimedia Mapping-Labor, NIG 1.Stock C0110
- Thursday 11.06. 12:30 - 15:30 Multimedia Mapping-Labor, NIG 1.Stock C0110
- Thursday 25.06. 12:30 - 15:30 Multimedia Mapping-Labor, NIG 1.Stock C0110
Information
Aims, contents and method of the course
This course provides an in-depth exploration of geospatial data and database management. Lectures introduce foundational concepts, including vector and raster data, spatial data integration, and spatial databases. Emphasis is placed on developing spatial thinking, with attention to key distinctions such as geometry versus topology and object-based versus field-based data modeling.Hands-on practical sessions primarily use Python and SQL. In these labs, students will develop proficiency with core Python libraries (e.g., GeoPandas) for spatial data, and gain experience working with PostGIS. The labs will also incorporate volunteered geographic information (VGI) sources, including OpenStreetMap.
Assessment and permitted materials
Participation (10%)
2 quizzes (30%)
1 midterm exam (30%)
1 final exam (30%)
2 quizzes (30%)
1 midterm exam (30%)
1 final exam (30%)
Minimum requirements and assessment criteria
Personal contribution that demonstrates an appropriate understanding of the approaches and methods discussed.100 % - 88 % = 1
87 % - 75 % = 2
74 % - 63 % = 3
62 % - 51 % = 4
Below 51 % = 5
87 % - 75 % = 2
74 % - 63 % = 3
62 % - 51 % = 4
Below 51 % = 5
Examination topics
Foundational topics, spatial thinking, and programming and database skills in geospatial data and data management
Reading list
1. Introduction to Python for Geographic Data Analysis: https://pythongis.org
2. Introduction to PostGIS: https://postgis.net/workshops/en/postgis-intro
3. Presentation and slides (including references)
2. Introduction to PostGIS: https://postgis.net/workshops/en/postgis-intro
3. Presentation and slides (including references)
Association in the course directory
(MK1-W1) (MK2) (MSDS-TS)
Last modified: Mo 27.07.2026 09:27