The recent introduction of mapping skills courses in numerous academic programs across various disciplines worldwide highlights the increasing importance of mapping as a fundamental literacy skill for a growing number of students. To optimize the learning outcomes for the CEU community, the 2-credit IGDV course is divided into two interconnected modules: IGDV-I (Basic) and IGDV-II (Advanced), each worth 1 credit. Successful completion of IGDV-I is a prerequisite for enrolling in IGDV-II, unless a student can demonstrate prior experience in geospatial visualization. This flexible structure allows students to enroll in either or both of the modules.

These courses are available to both undergraduate and graduate students, with the workload adjusted accordingly. For MAs/PhDs, the workload consists of 600 classroom minutes per credit, while for BAs, it amounts to 720 minutes per credit.

Successful completion of these course is a prerequisite for the Syslab’s winter semester courses, “Introduction to Geospatial Analysis” and “Earth Observations for Monitoring Sustainable Development Goals”, as well as Syslab’s internship and Summer University programs.

The course will feature collaboration activities with relevant courses at the American University of Central Asia and Bard College through the OSUN Network Collaborative Course program.

The aim of IGDV-I is to develop a basic understanding of Geographic Information Systems (GIS) principles, familiarize students with spatially referenced data, and cultivate fundamental skills in geospatial data visualization (mapping). While the course primarily focuses on practical mapping skills for societal and environmental phenomena, it also provides a brief introduction to alternative data collection technologies, such as satellite imagery, crowdsourcing, and expert knowledge. Various geospatial data file formats, including vector and raster, will be introduced. Many freely available geospatial datasets remain underutilized by researchers. Participants will learn about the types of data that can be stored in these datasets, as well as how to obtain, develop, and share them. Additionally, students will gain an understanding of map design considerations for different purposes, such as internet-based publications and journal articles.

The course will explore both desktop and online mapping solutions, including Google Earth Pro, Google Maps, and qGIS. QuantumGIS (qGIS), the most popular and widely used open-source GIS package, will serve as the primary software for illustrating geospatial data collection, generation, and visualization techniques. Through practical exercises using qGIS, participants will acquire the foundations of working with a typical GIS package and learn essential mapping principles.

The course will be organized as a series of short online presentations, followed by practical exercises and individual map development.

Learning Outcomes

By the end of the course, students should be able to:

• Understand the variety of data mapping approaches, their principles, and the benefits of their usage.
• Develop their own datasets based on different data sources such as statistics or expert knowledge.
• Create detailed topical maps using advanced features of qGIS.
• Consider alternative ways of collecting geospatial data, including online data mining and participatory science (geospatial data crowdsourcing).

Assessment

The course assessment is based on the following criteria:

• 30% Practical Sessions: Completion of several in-class exercises;
• 70% Graded Individual Project: Development and presentation of a mapping project.

Students are required to select a topic for their mapping project from a provided list or suggest their own.