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COURSE SYLLABUS

Data Visualization 7.5 credits

Visualisering av data
Second cycle, D7055E
Version
Course syllabus valid: Autumn 2021 Sp 1 - Present
The version indicates the term and period for which this course syllabus is valid. The most recent version of the course syllabus is shown first.


Education level
Second cycle
Grade scale
U G VG
Subject
Systems Science
Subject group (SCB)
Informatics/Computer and Systems Sciences
Main field of study
Information Systems Sciences

Entry requirements

In order to meet the general entry requirements for the course, you must have accomplished a minimum of 180 ECTS of university studies, out of which 60 ECTS in the areas of computer or system science. The studies shall have included Introductory Programming (for example D0009E Introduction to Programming or D0007N Objectoriented programming) and Fundamentals of Databases (for example D0004N Database Systems I or D0018E Database technology). Knowledge in English equivalent to English 6. More information about the English language requirements [http://www.ltu.se/edu/bli-student/Application-process/English-language-requirements-1.109316?l=en]


More information about English language requirements


Selection

The selection is based on 20-285 credits



Course Aim
The aim of the course for the student is to develop their knowledge and skills in data visualization. After completing the course, the student should be able to:
  1. Explain and use data visualization concepts
  2. Describe the data visualization techniques
  3. Explain how data visualization techniques are used to represent data in organizations
  4. Evaluate the use of certain data visualization
  5. Analyze and reflect on the results obtained via specific data visualization

Contents
The Data Visualization course is aimed at providing knowledge to the students with regards to how to represent data, visually. The course will enable students to connect to various datasets and sources while preparing for the visualization. Various topics and techniques will be explained in the course such as: use of colors, data-ink ratio, storytelling with graphs, and the taxonomy of data visualization methods. In a nutshell, the course aims to discuss the know-how to represent the data visually so as the visualization is appropriate, interactive, annotated, and using the right colors and graphical techniques.

Realization
Each course occasion´s language and form is stated and appear on the course page on Luleå University of Technology's website.
Lectures, lab hands-on, assignments, case studies and/or project work. During the course, the students work with individual tasks and/or group assignments for analysing, selecting and implementing different data visualization techniques. Some assignments or case studies in the course might contain work in contact with or about the industry. The student uses different methods and techniques, and it is important to choose the right method, technique or computer support for each task. Before and after the tasks are solved, there are lectures to present and discuss different solutions.

Teaching is in English and on the Internet for distance students or on campus for students living here. IT support: Learning management system, e-mail and phone.  The learning management system is used for delivering  course material, information and submissions. Knowledge is shared and created within the course through virtual meetings with teachers and other students for discussions, supervision, teamwork and seminars. For students on campus, there will be meetings on campus.

Examination
If there is a decision on special educational support, in accordance with the Guideline Student's rights and obligations at Luleå University of Technology, an adapted or alternative form of examination can be provided.
The course is examined as follows:

  • Written individual tasks and group tasks relating to the course aims 3-5, 6hp (U, G, VG)
  • Individual written exam relating to 1-2 of the course aims, 1.5hp (U, G, VG)

For a student to get VG in the whole course, a VG grade must be accomplished in the individual tasks and group tasks and in the individual written exam.

For the G grade, a student should achieve the grade G in the individual tasks and group tasks, as well as in the individual written exam.

Grades are given according to the scale: U, G, VG.

Remarks

  Technical Requirements: access to computer with administrative rights, web camera, microphone and Internet connection. 


Examiner
Ali Ismail Awad

Literature. Valid from Autumn 2020 Sp 1 (May change until 10 weeks before course start)
Title: Data Visualization: A Handbook for Data Driven Design
Author: Andy Kirk
Publisher: SAGE Publications, 1st edition, 2016

Title: Effective Data Visualization: The Right Chart for the Right Data
Author: Stephanie Evergreen
Publisher: SAGE Publications, 1st edition, 2016

Title: R Data Visualization Cookbook
Author: Atmajitsinh Gohil
Publisher: Packt Publishing - ebooks Accunt, 2015

Course offered by
Department of Computer Science, Electrical and Space Engineering

Modules
CodeDescriptionGrade scaleCrStatusFrom periodTitle
0005Individual tasks and group tasksU G VG6.00MandatoryA21
0006Written examU G VG1.50MandatoryA21

Study guidance
Study guidance for the course is to be found in our learning platform Canvas before the course starts. Students applying for single subject courses get more information in the Welcome letter. You will find the learning platform via My LTU.

Syllabus established
by Jonny Johansson, HUL SRT 21 Feb 2020

Last revised