Harokopio University
School: School of Digital Technology
Department: Informatics and Telematics
Program: Information Technology

Knowledge Management

Semester: 7 ECTS: 7.5 Elective Erasmus

General

Code: BSC_IT33

Language: English

Delivery: In person

Prerequisites: Databases

Workload

  • Lectures: 52.0 hours
  • Lab: 0.0 hours
  • Study: 75.5 hours
  • Project: 60.0 hours

Course Content

Basic Concepts of Mathematical Logic (Propositional, First-oder, Description Logics)
Data Representation in Relational Databases
NoSQL Databases
RDF and Triplestores
Ontologies, the OWL Language
Knowledge Graphs
Construction and Exploitation of Knowledge Graphs
Reasoning

Learning Outcomes

This course provides a comprehensive introduction to the principles and technologies used to transform raw data into structured, actionable knowledge. Starting from the formal foundations of Mathematical Logic, students will explore the evolution of data storage—from Relational and NoSQL databases to the specialized world of RDF and Triplestores. A significant portion of the course is dedicated to the "Semantic" layer of information, focusing on Ontologies (OWL) and the lifecycle of Knowledge Graphs, including their construction, exploitation, and the application of automated Reasoning to uncover hidden insights.

Upon successful completion of the course, students will be able to:
- understand and apply Propositional, First-order, and Description Logics as the basis for knowledge representation
- evaluate and implement various data models, including Relational, NoSQL, and Graph-based (RDF) systems
- design and develop formal Ontologies using the OWL language to define relationships and constraints within a domain
- construct, manage, and query Knowledge Graphs to integrate heterogeneous data sources.

Skills

Search for, analysis and synthesis of data and information, with the use of the necessary technology
Adapting to new situations
Decision-making
Working independently
Team work
Working in an international environment
Working in an interdisciplinary environment
Production of new research ideas
Project planning and management
Respect for difference and multiculturalism
Respect for the natural environment
Showing social, professional and ethical responsibility and sensitivity to gender issues
Criticism and self-criticism
Production of free, creative and inductive thinking
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Others…
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