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, 9
September 2025, Time: 12:15 – 14:00, Place:
Ag C233.1 (find more info in Moodle)
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Schedule (Fall, 2025):
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 the RDF-based semantic annotation of Web
resources and services for the Semantic Web, Linked Data and Ontology
Engineering; and also review some modern 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; 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.
Course-Related Context and Motivation:
The
Semantic Web is originated from Semantic Computing
which is an emergent field of Computing. It is a collaborative ongoing activity
led by the World Wide Web Consortium (W3C) to promote common data formats on
the World Wide Web specifically for machine-processable and machine understandable
data aiming to convert the current web, dominated by unstructured and
semi-structured documents, into a "web of data" (often referred as Web 3.0). The Semantic Web stack builds on the
W3C's Resource Description Framework (RDF). Publishing machine-understandable
data on the web is going as a mainstream. Linked Data (the activity originated
from the Semantic Web vision) has seen explosive growth over the past few
years. Linked Data assumes publishing structured data so that it can be
interlinked with standard Web technologies such as HTTP, RDF and URIs, aiming
to share information in a way that can be read automatically by computers. This
enables data from different sources to be connected and queried. For example,
DBPedia is a collection of data structured in RDF after being extracted from the Wikipedia, which allows Semantic Web-based applications
to automatically infer implicit or new data and make advanced queries over the
Wikipedia-derived dataset. The FOAF (Friend-of-a-Friend) is another example of
how the Semantic Web attempts to make use of the data about people and their
relationships within a social context. Organization of data based on RDF
(graph) model makes it possible to connect data from distinct heterogeneous
sources, organize and query huge volumes (Big Data challenge) of data.
Ontologies are helpful to provide interoperability among various schemas used
in the data and enable applications automatically discover and explore new
previously unknown sources of data. Semantic-Web-standards-driven so-called
Semantic Technology as a software technology allows the meaning of information
to be known and processed at execution time of various applications making them
naturally interoperable in the Web and within various digital ecosystems and
clouds. Therefore as a summary: the Semantic Web is an evolving development of
the World Wide Web in which the meaning (semantics) of information and services
published on the Web and their inter-relationships are explicitly defined,
making it possible for the Web-based software tools, agents, applications and
systems to discover, extract and “understand” Web information resources and
capabilities and automatically utilize it. Related to these, the Linked Data activity aims to expose, share, and connect distributed
pieces of data, information, and knowledge; to extend the Web by publishing
various open datasets and by setting semantic links between data items from
different data sources. The Semantic Web vision assumes annotating Web
resources with machine-interpretable descriptions (metadata) referred to shared conceptual vocabularies (ontologies), and
provides mechanisms for automated reasoning about them.
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
slightly 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!