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Information
| Code | CENG0043 |
| Name | Data Visualization |
| Term | 2023-2024 Academic Year |
| Term | Fall |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | İngilizce |
| Level | Yüksek Lisans Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Dr. Öğr. Üyesi Elif Emel FIRAT |
| Course Instructor |
1 |
Course Goal / Objective
To introduce students to fundamental problems, concepts and approaches in the design and analysis of data visualization systems.
Course Content
Familiarize students with the phases of the visualization pipeline, including data modeling, mapping data attributes to graphical attributes, perceptual issues, available visualization techniques and tools, and evaluating the effectiveness of visualizations for specific data, tasks, and user types.
Course Precondition
None
Resources
Wilke, C.O., 2019. Fundamentals of data visualization: a primer on making informative and compelling figures. O'Reilly Media.
Notes
Chen, Chun-houh, Wolfgang Karl Härdle, and Antony Unwin, eds. Handbook of data visualization. Springer Science & Business Media, 2007. Chen, Chun-houh, Wolfgang Karl Härdle, and Antony Unwin, eds. Handbook of data visualization. Springer Science & Business Media, 2007.
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | The student understands the fundamentals and properties of data. |
| LO02 | The student knows the various available visualization systems and tool sets. |
| LO03 | The student knows the design considerations for the components of good visualization. |
| LO04 | The student detects the trend in the data by creating visual designs. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | On the basis of the competencies gained at the undergraduate level, it has an advanced level of knowledge and understanding that provides the basis for original studies in the field of Computer Engineering. | 3 |
| PLO02 | Bilgi - Kuramsal, Olgusal | By reaching scientific knowledge in the field of engineering, he/she reaches the knowledge in depth and depth, evaluates, interprets and applies the information. | 3 |
| PLO03 | Yetkinlikler - Öğrenme Yetkinliği | Being aware of the new and developing practices of his / her profession and examining and learning when necessary. | 2 |
| PLO04 | Yetkinlikler - Öğrenme Yetkinliği | Constructs engineering problems, develops methods to solve them and applies innovative methods in solutions. | 3 |
| PLO05 | Yetkinlikler - Öğrenme Yetkinliği | Designs and applies analytical, modeling and experimental based researches, analyzes and interprets complex situations encountered in this process. | 4 |
| PLO06 | Yetkinlikler - Öğrenme Yetkinliği | Develops new and / or original ideas and methods, develops innovative solutions in system, part or process design. | 3 |
| PLO07 | Beceriler - Bilişsel, Uygulamalı | Has the skills of learning. | 3 |
| PLO08 | Beceriler - Bilişsel, Uygulamalı | Being aware of new and emerging applications of Computer Engineering examines and learns them if necessary. | |
| PLO09 | Beceriler - Bilişsel, Uygulamalı | Transmits the processes and results of their studies in written or oral form in the national and international environments outside or outside the field of Computer Engineering. | 4 |
| PLO10 | Beceriler - Bilişsel, Uygulamalı | Has comprehensive knowledge about current techniques and methods and their limitations in Computer Engineering. | |
| PLO11 | Beceriler - Bilişsel, Uygulamalı | Uses information and communication technologies at an advanced level interactively with computer software required by Computer Engineering. | 3 |
| PLO12 | Bilgi - Kuramsal, Olgusal | Observes social, scientific and ethical values in all professional activities. |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Fundamentals of data | Reading lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 2 | Perception and Information Processing | Reading lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 3 | Fundamentals of visualization | Reading lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 4 | Visualization techniques for spatial data | Reading lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 5 | Visualization techniques for geographical data | Reading lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 6 | Visualization techniques for timeoriented data | Reading lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 7 | Visualization techniques | Reading lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 8 | Mid-Term Exam | Readinglecture notes | Ölçme Yöntemleri: Ödev |
| 9 | Visualization techniques for trees, graphs, and networks | Reading lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 10 | Interaction concepts | Reading lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 11 | Interaction techniques | Reading lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 12 | Designing effective visualizations | Reading lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 13 | Continue designing effective visualizations | Reading lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 14 | Article presentations | Article scanning, presentation preparation | Öğretim Yöntemleri: Bireysel Çalışma, Örnek Olay, Soru-Cevap |
| 15 | Project presentations | Project preparation, presentation preparation | Öğretim Yöntemleri: Bireysel Çalışma, Proje Temelli Öğrenme |
| 16 | Term exam preparations | Reading lecture notes | Öğretim Yöntemleri: Soru-Cevap |
| 17 | Term Exams | Reading Lecture Notes | Ölçme Yöntemleri: Yazılı Sınav |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 4 | 56 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 2 | 15 | 30 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 10 | 10 |
| Final Exam | 1 | 20 | 20 |
| Total Workload (Hour) | 158 | ||
| Total Workload / 25 (h) | 6,32 | ||
| ECTS | 6 ECTS | ||