Semantic Web and
Linked Data
(Course
code: ITKS5440) 5 ECTS;
Fall Semester
Previous (before Autumn,
2017) name of the course:
Semantic Web and Ontology Engineering
(Course code: ITKS544) 5 ECTS; Fall Semester
Instructor:
Vagan Terziyan
Email: vagan.terziyan@jyu.fi
(Register for
the course in SISU
system)
The course is lectured in English.
Attention: 1-st Lecture: Tuesday, 8 September 2026,
Time: 12:15 – 14:00, Place: Ag B121.1
(find more info in Moodle)
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Schedule (Fall, 2026):
THIS COURSE IS INDEPENDENT PART OF OUR ARTIFICIAL
INTELLIGENCE COURSES’ PACKAGE; IT DOES NOT REQUIRE ANY PREQUESITIES AND CAN
BE STUDIED REMOTELY (SELF-STUDY BASED ON PROVIDED MATERIAL)
Personal quota from
the course instructor:
“Everything will
be Artificial Intelligence soon, and, instead of being worried about it and
restricting it (which is a bad idea), come to study, develop, use, and promote
it further!”
Overview:
ITKS-5440: Semantic Web and Linked Data (5 ECTS)
Course Summary:
Artificial
Intelligence has two major sides, which complement each other: the Bottom-Up AI
driven by Machine (also Deep) Learning; and the Top-Down AI driven by
formalized human knowledge. This course (ITKS-5440: Semantic Web and Linked
Data) corresponds to the Top-Down AI family of approaches and includes an
introduction and practical tutorial on Knowledge Graphs, RDF-based semantic annotation of
everything for the Semantic Web, Linked Data, Knowledge Graphs, and Ontology
Engineering; and also review some applications of these methods and techniques
for Web-based intelligent applications and services.
Main Content Components
Semantic
Web mission; concepts of semantic interoperability, integration and automation;
concept of metadata and ontology; Semantic Web standards; RDF (Resource
Description Framework); Linked Data; Knowledge Graphs; Ontology Engineering;
OWL (Web Ontology Language); Rules for inferring knowledge; SWRL (Semantic Web
Rules Language); Semantic Technology; Semantic (Web) Applications and Services;
Relation to Big Data and Industry 4.0 (5.0).
Course-Related Context and Motivation:
Relation of the course with Master Programs of the
Faculty of Information Technology:
Master
Program on Artificial Intelligence is the
natural place for such course because this Program
explores different aspects and services from Deep Learning, Big Data analytics
and Web-based Cognitive Computing, which require Semantic (Web) Technology to
enable self-management and to handle heterogeneity of information, technology
capabilities and users. Learning outcomes of this course are assumed to be an
input to several other courses of the AI, WISE and COIN programs (e.g., https://ai.it.jyu.fi/vagan/courses.html, Deep Learning for Cognitive Computing, SOA
and Cloud Computing; Design of Agent-Based Systems; Collective Intelligence and
Agent Technology; Interface of Things; Big Data Engineering and others).
Among
other Master programs the closest one is Data
Analysis (or similar) program as the course provides the framework and
advertises tools for machine-processable data in the Web.
The course is also suitable for the Cyber Security (or similar) Master
Program as it is known that the so-called “Web of Trust” is one of the ultimate
goals of the Semantic Web. Research on the topic of trust in this domain has
focused largely on digital signatures, certificates, and authentication as well
as trust in social networks.
The Software
Engineering Master Program can benefit from the semantic
technology, semantic programming, semantic applications, self-managed systems
engineering, and the open world assumption in software design originated from
the Semantic Web vision and based on appropriate standards.
The best evidence on having the
ITKS-5440 course naturally relevant to most of master programs of the MIT
department (e.g., Data Analysis, Cyber Security, variations of Computational
Science, and others) is given by Amit Sheth (h-index > 80) in http://amitsheth.blogspot.fi/2007/10/what-is-semantic-computing.html as follows: “Semantic computing is a vision of computing
based on semantics shared between machines and people. It supports and exploits
intrinsic, intended, and emergent meanings (content) in all aspects of
computing, encompassing programming, algorithms, information management, and
human interactions within devices, as part of communications, and across the
Web. Semantics involves the use of formal descriptions, languages, and models,
often encoded in metadata, knowledge, and representation of agreements (as in
ontologies) to capture the content of multimedia, texts, services, and
structured data so that it may be extracted, shared, synthesized and
transformed. Semantic techniques foster the development emerging forms of
computing, such as semantic Web, and entirely new forms, such as bio-inspired
computing, as well as enhance traditional techniques of information retrieval,
management of data (including multimedia and multimodal) and artificial
intelligence (e.g., natural language processing machine learning, and
computational intelligence), leading to more efficient and scalable information
processing and higher-quality computer-human interaction.”
Lecture Notes:
Lectures 3-4-5-6:
Semantic Web Basics and Applications
Lectures
7-8-9-10: Tutorial on Designing Ontologies with Protégé (see also: Presentation
1 and Presentation
2), for the newer versions of Protégé, check Protégé
- tutorial Documentation
Recorded Video-Lectures from the
former years of teaching:
can be downloaded and
viewed from Moodle.
NOTE: if you have possibility to come
to the in-class lectures, choose this option, because lecture content is
constantly updated, and the recorded lectures from previous years could be
outdated …
Exercise/Assignment
·
Create
your CV as part of your personal Web page preferably in your personal Web space
provided by the university account, for example: http://users.jyu.fi/~abcdefgh/cv.html;
·
create
ontology with OWL (using Protégé ontology editing tool) needed for describing
humans, entities, organizations, events, records, abstractions, etc., mentioned
in your CV (or CVs like yours). In addition to your own ontology, you can
import other publicly available ontologies and merge them with your ontology;
·
semantically
describe (annotate) yourself as a Web resource (with unique URI) following the
story presented in your CV (together with other resources mentioned in it:
people, universities, schools, companies, places, skills, files, documents,
records, etc.) using RDF (link yourself with other relevant Web resources or
physical World resources according to the ontology created in Protégé). In
Protégé, the semantic annotation process means just creating a new instance in appropriate
class and feeling with data (put values to slots) the form prepared by the
ontology;
·
please, do not provide any
private/sensitive information, which is not meant to be shared in the Web;
·
it will
be appreciated if some (the more – the better) of these “other resources” in
the neighbourhood of the target person will be found in and connected with
other well-known open metadata repositories, such as, e.g., DBPedia
(https://wiki.dbpedia.org/ see also: http://dbpedia.org/sparql );
·
the group
of “other resources” may include various types of media files (relevant texts,
photos, videos, etc.) available in the Web;
·
for doing
the task above, please download and install
version Protégé 5.5 (or later versions) from: http://protege.stanford.edu ;
·
your
Protégé project will combine (in the same OWL file) both: the ontology and the
RDF semantic annotations ;
·
(!) please
be very careful by specifying your ontology URI. It should correspond exactly
to the Web URL of the ontology (depends on your personal Web space). For
example: http://users.jyu.fi/~abcdefgh/cv-ontology.owl
;
·
when you
save your project for the first time make sure that the name of the file will
correspond to the one from the URI (e.g.: cv-ontology.owl for the example above);
·
when finished
working with Protégé do not forget to upload the cv-ontology.owl file to your
personal Web space so that its URLs will look like: http://users.jyu.fi/~abcdefgh/cv-ontology.owl
.
·
provide
report (e.g. in DOC file, where name of
file is student’s capitalized family name), which consists at least of: (A) full name of the student; (B) name of
the course; (C) the URL of the original CV (e.g., http://users.jyu.fi/~abcdefgh/cv.html); (D) the link to the ontology file (e.g., http://users.jyu.fi/~abcdefgh/cv-ontology.owl; and (E) the Conclusion;
·
In
“Conclusion” part of the report please write your opinion, by which possible
way (by what kind of applications) the semantic annotation of yourself
according to the CVs and the appropriate ontology can be used;
·
Do not
remove appropriate files from the Web until final decision will be made;
·
Files
with report should be sent by e-mail to Vagan Terziyan until 15 November;
·
Notification
of evaluation - until 25 November.
Collaborate
with our research group on developing stronger AI!