Computer Engineering
Course Details
KTO KARATAY UNIVERSITY
Mühendislik ve Doğa Bilimleri Fakültesi
Programme of Computer Engineering
Course Details
Mühendislik ve Doğa Bilimleri Fakültesi
Programme of Computer Engineering
Course Details
| Course Code | Course Name | Year | Period | Semester | T+A+L | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| 05081460 | Introduction To Semantic Web | 4 | Spring | 8 | 3+0+0 | 3 | 5 |
| Course Type | Elective |
| Course Cycle | Bachelor's (First Cycle) (TQF-HE: Level 6 / QF-EHEA: Level 1 / EQF-LLL: Level 6) |
| Course Language | Turkish |
| Methods and Techniques | - |
| Mode of Delivery | Face to Face |
| Prerequisites | - |
| Coordinator | - |
| Instructor(s) | Asst. Prof. Ali Osman ÇIBIKDİKEN |
| Instructor Assistant(s) | - |
Course Instructor(s)
| Name and Surname | Room | E-Mail Address | Internal | Meeting Hours |
|---|---|---|---|---|
| Asst. Prof. Ali Osman ÇIBIKDİKEN | A-124 | [email protected] | 7585 | Monday 14.00-15.00 |
Course Content
At the end of the course the student should be able to: understand and discuss fundamental concepts, advantages and limits of the semantic web; understand and use ontologies in the context of Computer Science and the semantic web; use the RDF framework and associated technologies such as RDFa; understand the relationship between Semantic Web and Web 2.0.
Objectives of the Course
The aim of this course is to teach the students the concepts, technologies and techniques underlying and making up the Semantic Web.
Contribution of the Course to Field Teaching
| Basic Vocational Courses | |
| Specialization / Field Courses | |
| Support Courses | X |
| Transferable Skills Courses | |
| Humanities, Communication and Management Skills Courses |
Relationships between Course Learning Outcomes and Program Outcomes
| Relationship Levels | ||||
| Lowest | Low | Medium | High | Highest |
| 1 | 2 | 3 | 4 | 5 |
| # | Program Learning Outcomes | Level |
|---|---|---|
| P3 | Ability to design a complex system, process, device or product to meet specific requirements under realistic constraints and conditions; ability to apply modern design methods for this purpose | 4 |
| P5 | An ability to design, conduct experiments, collect data, analyze and interpret results for the study of complex engineering problems or disciplinary research topics | 5 |
Course Learning Outcomes
| Upon the successful completion of this course, students will be able to: | |||
|---|---|---|---|
| No | Learning Outcomes | Outcome Relationship | Measurement Method ** |
| O1 | Knowledge of algorithm design and analysis techniques. | P.3.1 | |
| O2 | Knowledge of algorithm design and analysis techniques. | P.2.14 | 1 |
| O3 | Knowledge of processor structure and operating logic. | P.3.21 | |
| O4 | Data analysis | P.2.22 | 2 |
| O5 | Algorithm | P.2.23 | 7 |
| ** Written Exam: 1, Oral Exam: 2, Homework: 3, Lab./Exam: 4, Seminar/Presentation: 5, Term Paper: 6, Application: 7 | |||
Weekly Detailed Course Contents
| Week | Topics |
|---|---|
| 1 | Introduction to the Semantic Web |
| 2 | Introduction to Ontologies |
| 3 | Ontology Languages for the Semantic Web |
| 4 | Resource Description Framework (RDF) |
| 5 | Lightweight ontologies: RDF Schema |
| 6 | Web Ontology Language (OWL) |
| 7 | Ontology Engineering |
| 8 | Semantic web and Web 2.0 |
| 9 | Examination of non-blocking I/O structures |
| 10 | Examination of raw socket structures |
| 11 | Network application examples with Java programming language |
| 12 | Network application examples with Java programming language |
| 13 | Reminding |
| 14 | exam |
Textbook or Material
| Resources | The Semantic Web Michael C. Daconta, Leo J. Obrst, Kevin T. Smith 2003, ISBN: 0471432571 Kitap-2:Semantic Web for the Working Ontologist Dean Allemang, James Hendler 2008, ISBN: 9780123735560 |
Evaluation Method and Passing Criteria
| In-Term Studies | Quantity | Percentage |
|---|---|---|
| Attendance | - | - |
| Laboratory | - | - |
| Practice | - | - |
| Course Specific Internship (If Any) | - | - |
| Homework | - | - |
| Presentation | - | - |
| Projects | - | - |
| Quiz | - | - |
| Midterms | 1 | 40 (%) |
| Final Exam | 1 | 60 (%) |
| Total | 100 (%) | |
ECTS / Working Load Table
| Quantity | Duration | Total Work Load | |
|---|---|---|---|
| Course Week Number and Time | 14 | 3 | 42 |
| Out-of-Class Study Time (Pre-study, Library, Reinforcement) | 14 | 5 | 70 |
| Midterms | 1 | 3 | 3 |
| Quiz | 0 | 0 | 0 |
| Homework | 0 | 0 | 0 |
| Practice | 0 | 0 | 0 |
| Laboratory | 0 | 0 | 0 |
| Project | 0 | 0 | 0 |
| Workshop | 0 | 0 | 0 |
| Presentation/Seminar Preparation | 0 | 0 | 0 |
| Fieldwork | 0 | 0 | 0 |
| Final Exam | 1 | 3 | 3 |
| Other | 14 | 3 | 42 |
| Total Work Load: | 160 | ||
| Total Work Load / 30 | 5,33 | ||
| Course ECTS Credits: | 5 | ||
Course - Learning Outcomes Matrix
| Relationship Levels | ||||
| Lowest | Low | Medium | High | Highest |
| 1 | 2 | 3 | 4 | 5 |
| # | Learning Outcomes | P2 | P3 |
|---|---|---|---|
| O1 | Knowledge of algorithm design and analysis techniques. | 3 | - |
| O2 | Data analysis | - | 5 |
| O3 | Algorithm | 2 | 4 |
| O4 | Knowledge of algorithm design and analysis techniques. | - | 1 |
| O5 | Knowledge of processor structure and operating logic. | 3 | - |