Information Package

Master's of Visual Communication Design with Thesis

GİT519

DATA VISUALIZATION

Course Code
GİT519
Semester
-
Theory+Practice
3 + 0
ECTS
10
Course TypeElective Course
Course LevelMaster's Degree With Thesis
Year of Study-
Semester-
ECTS10
Name of Lecturer(s) -
Learning Outcomes

At the end of this course, the students;

  1. Learn the process of creating meaning by visualizing data,
  2. Develop the narrative of data visualization through art,
  3. Learn data visualization techniques.
Mode of DeliveryFace to face
PrerequisitesNo
Recommended Optional Programme Components
Course DescriptionThis course covers the fundamentals of information architecture and presentation, the transformation of data into information, concepts such as relationship, grouping and hierarchy, cognitive information processing processes, shaping, presenting and visualizing information for different media and through different cases, recipe design, time series, location-time data, comparison and big data, interaction methods based on information and touch, gestures and devices.
Course Contents
WEEK TOPICS
1st Week Introduction and general information about course content/operation
2nd Week Data Visualization reality definitions
3rd Week Information processing and visualization processes
4th Week Data Analysis and visualization examples in the Visual Communication Design Field
5th Week Sample application within the scope of the course
6th Week Program usage and Visualization Types
7th Week Project Idea Discussion
8th Week Project Development Stage I
9th Week Project Development Stage II
10th Week Project Development Stage III
11th Week Project Development Stage IV
12th Week Project Development Stage V
13th Week Project Development Stage VI
14th Week Project Development Stage VII
Recommended or Required ReadingÇelik, S., & Akdamar, E. (2018). Büyük veri ve veri görselleştirme. Akademik Bakış Uluslararası Hakemli Sosyal Bilimler Dergisi, (65), 253-264.
GÜRLER, A., YILMAZ, A. S., & TEKEREK, M. (2018). Veri görselleştirme ve infografikler. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi, 21(2), 131-148.
Planned Learning Activities and Teaching Methods
  • Lecture
  • Case Study
  • Project
Assessment Methods and Criteria
Quantity Percentage (%)
Mid-term 1 40
Attendance 1 10
Total(%) 50
Contribution of In-term Studies to Overall Grade(%) 50
Contribution of Final Examination to Overall Grade(%) 50
Total(%) 100
ECTS Allocated Based on Student Workload
Activities Quantity Duration (Hour) Total Workload (Hour)
Midterm exam 1 3 3
Preparation for Quiz 3 3 9
Individual or group work 14 3 42
Preparation for Final exam 4 3 12
Course hours 14 4 56
Preparation for Midterm exam 2 4 8
Laboratory (including preparation) 14 4 56
Final exam 1 3 3
Homework 10 1 10
Presentation (including preperation) 1 3 3
Project 2 3 6
Quiz 3 3 9
Field Research 1 2 2
Meeting with advisor 13 1 13
Material Development 14 2 28
Book Presentation 14 1 14
Article Presentation 12 1 12
Case Study Presentation 14 1 14
Total Work Load300
Total Work Load / 30 (h)10
ECTS Credit of the Course10
Language of InstructionTurkish
Work Placement(s)No
LO1 LO2 LO3
K1 X X X
K2 X X
K3 X
K4
K5
K6
K7
K8 X X X
K9
K10
K11
K12 X X X
K13
K14 X X X
K15 X X X