ACIT4011 Graph Data Management Course description

***The course doesnt run spring2026 semester

In today's data-driven world, the effective management of graph data has emerged as a vital skill across various domains, including business, technology, and sciences. Graphs provide a powerful way to represent and analyse interconnected data, and they play a crucial role in fields such as complex systems and network science, social sciences, biology and genetics, and more.

In the area of Artificial Intelligence and Data Science, graph databases enable the modelling of complex relationships between data points, enhancing machine learning algorithms and data analysis techniques. Application areas such as social media can benefit greatly from graph databases as they allow for efficient representation and querying of complex relationships between entities, such as the connections between users, their interactions, and shared content, making them an ideal choice for such applications.

This course focuses on Graph Data Management, covering the fundamentals of creating, organising, querying, and deriving insights from graph-structured data. With the exponential growth of interconnected data sources, the need for skilled professionals who can navigate graph data, construct knowledge graphs, leverage graph databases, perform graph analytics, and contribute to the emerging field of Graph Data Science has become increasingly evident. This course equips students with the foundational knowledge and skills required to work with graph data.

This course encompasses topics such as graph data concepts and representations, building and constructing knowledge graphs, exploring graph databases and their applications, graph querying, graph analytics.

Databases and Programming

No formal requirements over and above the admission requirements.

A student who has completed this course should have the following learning outcomes defined in terms of knowledge, skills and general competence.

Knowledge

The student has:

• understanding of graph data and its characteristics
• familiarity with constructing and modelling knowledge graphs
• awareness of graph analytics techniques

Skills

The student can:

• use graph databases for efficient data storage and retrieval
• create, manipulate, and manage graph data
• design and implement graph-based data management processes
• employ graph analytics for complex data exploration

General competence

The student can:

• optimise data organisation through graph-based representations
• evaluate and select appropriate graph-based solutions for various tasks
• articulate the significance of graph data management in diverse domains.

This is a project-based course, divided into two parts, with focus on basics of graph data management at the beginning and student project work towards the end. The forms of teaching will include lectures, group discussions, and project work.

The following required coursework must be approved before the student can take the exam:

Students will collaborate in groups (approx. 2-5 students per group) to plan, execute, and report on one graph data project. The deliverable consists of two parts:

1. a group project proposal (700 - 1000 words) on the assigned topic, containing project description, the available dataset(s), method/algorithm to be employed, and relevant references.
2. a group oral presentation on the project proposal of the assigned topic.

The final assessment consists of two parts:

1. A group project implementation (approx. 2-5 students per group), including a project report (3000 - 5000 words, excluding references) and code/data as an appendix (counts 70% towards the final grade). Both the code/data and the report will be evaluated.
2. A 15-minute group presentation of the project (counts 30% towards the final grade).

Both parts must be passed in order to pass the course. The oral exam cannot be appealed.

New/postponed exam

In case of failed exam or legal absence, the student may apply for a new or postponed exam. New or postponed exams are offered within a reasonable time span following the regular exam. The student is responsible for registering for a new/postponed exam within the time limits set by OsloMet. The Regulations for new or postponed examinations are available in Regulations relating to studies and examinations at OsloMet.

All aids are permitted.

Grade scale A - F.

Exam part 1 (group proposal): one internal examiner

Exam part 2 (oral exam): two internal examiners

External examiners are used periodically.

Prof. Dumitru Roman