MK EN
ФИНКИ

Web Based Systems

1.Course titleWeb Based Systems
2.CodeF23L3W079
3.Study programme
4.Organizer of the study programme (unit, institute, department)Faculty of Computer Science and Engineering
5.Degree level (first, second, third cycle)First cycle
6.Academic year / semester7 / Winter
7.Number of ECTS credits6
8.Teacher
9.Prerequisites for enrolling in the courseАлгоритми и податочни структури или Примена на алгоритми и податочни структури
10.Course objectives (competences)Introduction and use of Semantic Web, Linked Data, and Knowledge Graph technologies. Students will learn to develop intelligent applications based on knowledge graphs and to find and use open data sets.
11.Course contentLectures:
1. Semantic Web
2. Basic protocols and standards in Semantic Web (RDF, RDFS, OWL)
3. Development of ontologies (Analysis, reuse, Design, Meta data, knowledge base)
4. Open data
5. Related Data
6. Schema.org as a concept for global communication.
7. Using Big Data Sets (DBPedia)
8. Knowledge graphs
9. Creating knowledge graphs from textual data
10. Machine learning with graphs
11. Graph-neural networks
12. Graph neural networks in knowledge graphs
13. Intelligent applications based on data and visualization of knowledge graphs

Exercises:
1. Describing web documents with RDF
2. RDF Schema
3. Libraries for working with RDF data
4. Query language for RDF data: SPARQL
5. Web Ontologies Language: OWL
6. Development of ontologies
7. Introduction to the concept of linked data and knowledge graphs
8. Consuming linked data and knowledge graphs
9. Creating linked data and knowledge graphs
10. RDF databases and RDF datasets
11. Publishing related data and knowledge graphs
12. Statistical and machine analysis of knowledge graphs
13. Intelligent applications based on data and visualization of knowledge graphs (exercises)
12.Learning methodsLectures supported by slide presentations, interactive lectures, practical classes (using equipment and software packages), teamwork, case studies, guest lecturers, independent preparation and defence of a project assignment and seminar paper, and learning in an electronic environment (forums and consultations).
13.Total available time6 ECTS x 30 hours = 180 hours
14.Distribution of the available time30 + 45 + 15 + 15 + 75 = 180 hours
15.Forms of teaching activities
15.1.Lectures – theoretical teaching30 hours
15.2.Exercises (laboratory, auditory), seminars, team work45 hours
16.Other forms of activities
16.1.Project assignments15 hours
16.2.Individual assignments15 hours
16.3.Home study75 hours
17.Grading
17.1.Tests0 points
17.2.Seminar paper / project (presentation: written and oral)15 points
17.3.Activity and participation15 points
17.4.Final exam65 points
18.Grading criteria (points / grade)
up to 50 points5 (five) (F)
from 51 to 60 points6 (six) (E)
from 61 to 70 points7 (seven) (D)
from 71 to 80 points8 (eight) (C)
from 81 to 90 points9 (nine) (B)
from 91 to 100 points10 (ten) (A)
19.Requirements for signature and taking the final examcompleted activities 15.1 and 15.2
20.Language of instructionMacedonian and English
21.Method of monitoring teaching qualityinternal evaluation and survey mechanism
22.Literature
22.1.Required literature
1. Péter Szeredi, Gergely Lukácsy, Tamás Benkő, Zsolt Peter Nagy | The Semantic Web explained: The Technology and Mathematics Behind Web 3.0 | Cambridge: Cambridge University Press | 2014
2. David Wood | Linked Data: Structured Data on the Web | Manning Publications Co | 2014
3. Leslie Sikos | Mastering Structured Data on the Semantic Web: From HTML5 Microdata to Linked Open Data | Apress | 2015
4. Aidan Hogan et al. | Knowledge Graphs | Morgan & Claypool | 2021
22.2.Additional literature
No. Author Title Publisher Year
Деканат Dean’s Office Студии Studies Акти Acts Проекти Projects