Graduate study programme

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Data visualization DRcd2-03

ECTS 5 | P 30 | A 0 | L 15 | K 15 | ISVU 149826 | Academic year: 2019./2020.

Course groups

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Course lecturers

JOB JOSIP, Lecturer
LIVADA ČASLAV, Associate

Goals

Introduce students to theoretical and practical knowledge in the field of data visualisation. Teach them how to use and to work with data visualisation tools and libraries. Train them to work individually and within team on data visualisation projects, and enable critical thinking and evaluation of data visualisation.

Conditions for enrollment

Requirements met for enrolling in the study programme

Course description

Introduction to data visualisation, importance of data visualisation: storage of information, decision support, information transfer. Data types. Nominal, ordinal and quantitative data. Dimensions and measures. Visual encoding variables. Data visualisation reference model. Data visualisation design. Data analysis. Visualisation of multidimensional data. Perception, human visual system, Gestalt psychology. Interaction. Animation. Cartography. Graphs and trees. Colours. Narrative visualisation. Text visualisation. Evaluation of data visualisation. Data visualisation tools.

Student requirements

Defined by the Student evaluation criteria of the Faculty of Electrical Engineering, Computer Science and Information Technology Osijek and paragraph 1.9

Monitoring of students

Defined by the Student evaluation criteria of the Faculty of Electrical Engineering, Computer Science and Information Technology Osijek and paragraph 1.9

Obligatory literature

1. 1 E. R. Tufte The Visual Display of Quantitative Information, 2nd edition Graphics Press, Cheshire, 2001.

2. 2 Murray, S. Interactive Data Visualization for the Web O Reilly, 2013.


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Recommended additional literature

1. 1 M. Maclean D3 Tips & Tricks M. Maclean, 2014.

Course assessment

Conducting university questionnaires on teachers (student-teacher relationship, transparency of assessment criteria, motivation for teaching, teaching clarity, etc.). Conducting Faculty surveys on courses (upon passing the exam, student self-assessment of the adopted learning outcomes and student workload in relation to the number of ECTS credits allocated to activities and courses as a whole).

Overview of course assesment

Learning outcomes
Upon successful completion of the course, students will be able to:

1. indicate and describe the basic elements of visualization

2. design and create one's own data visualisation using appropriate tools and software libraries

3. propose design of data visualisation in line with good practice and in accordance with the theoretical basis

4. interpret and analyse data visualization design



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