Graph Related Data Analytics
2025/2026
Content, progress and pedagogy of the module
Disclaimer
This is an English translation of the module. In case of
discrepancy between the translation and the Danish version, the
Danish version of the module is valid.
PURPOSE
Graph-related data appears in many contexts, such as the web,
social networks, communication, transport, and digital energy. The
purpose of the project module is for the student to gain insight
into how methods and technologies for analyzing graph-related data
can be applied in relevant practical applications.
JUSTIFICATION
Graphs allow for the modeling of a wide range of relationships, and
graph-related data appears in many important IT applications, such
as the web, social networks, communication, and transport.
Graph-related data can include, for example, spatial and temporal
references and can encompass text data. It is often important to be
able to analyze graph-structured data.
Learning objectives
Knowledge
demonstrate knowledge of methods and technologies for analyzing graph-structured data
demonstrate insight into important characteristics of methods and technologies for analyzing graph-structured data
demonstrate insight into the applicability of methods and technologies for analyzing different types of graph-structured data
Skills
identify and represent graph-related data for subsequent analysis, including, for example, data fusion and integration
apply relevant methods and technologies for analyzing graph-related data to solve specific problems
integrate analysis solutions into an application that solves a concrete problem
argue for and reflect on the choices of methods and technologies in an application
Competences
reflect on the applicability of a solution that involves the analysis of graph-related data
reflect on the possibilities and limitations of different methods and technologies for analyzing graph-related data
Type of instruction
Project work, the project must include:
analysis of a problem
design, implementation, and evaluation of an application that uses the analysis of graph-related data to solve a problem
reflection on the developed solution
Extent and expected workload
The student is expected to spend 30 hours per ECTS, which for this activity means 450 hours.
Exam
Exams
| Name of exam | Graph Related Data Analytics |
| Type of exam | Oral exam based on a project |
| ECTS | 15 |
| Permitted aids | Aids are permitted during the preparation of the project, but not during the exam. Rules regarding AI are mentioned on the semester page in MOODLE |
| Assessment | 7-point grading scale |
| Type of grading | External examination |
| Criteria of assessment | The criteria of assessment are stated in the Examination Policies and Procedures |
Additional information
Contact: Study Board for Computer Science via cs-sn@cs.aau.dk or 9940 8854
Facts about the module
| Danish title | Analyse af graf-relaterede data |
| Module code | DSNDVMLB531 |
| Module type | Project |
| Duration | 1 semester |
| Semester | Autumn
|
| ECTS | 15 |
| Language of instruction | Danish and English |
| Location of the lecture | Campus Aalborg |
| Responsible for the module |
Organisation
| Education owner | Bachelor of Science (BSc) in Data Science and Machine Learning |
| Study Board | Study Board of Computer Science |
| Department | Department of Computer Science |
| Faculty | The Technical Faculty of IT and Design |
