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Visual Analytics

* Exchange students do not have to consider this information when selecting suitable courses for an exchange stay.

Course Unit Code548-0142/02
Number of ECTS Credits Allocated4 ECTS credits
Type of Course Unit *Compulsory
Level of Course Unit *Second Cycle
Year of Study *First Year
Semester when the Course Unit is deliveredWinter Semester
Mode of DeliveryFace-to-face
Language of InstructionEnglish
Prerequisites and Co-Requisites There are no prerequisites or co-requisites for this course unit
Name of Lecturer(s)Personal IDName
IVA026prof. Ing. Igor Ivan, Ph.D.
Summary
The course will explain to students the issue of visual analytics, which is becoming a highly attractive topic due to the development of large data sets. Students are acquainted with the history, development and current trends in this area. Possibilities of interactive data visualization based on their type using more common and non-traditional and complex approaches are presented. Emphasis is placed on determining the suitability of individual visualization methods and evaluating weaknesses and possible problems. Students are introduced to 2D and 3D space-time visualization methods and their use in geoinformatics.
Learning Outcomes of the Course Unit
- the student demonstrates knowledge of:
• issues of visual analytics,
• existing channels and marks in visualization,
• suitable visualization tools according to the type of data,
• interactivity options for data visualization,
• automatic analytics support;
- the student is able to:
• choose a suitable visualization method for multivariate, temporal, spatial, textual and graph data,
• evaluate a suitable visualization technique,
• analyze large data using interactive visualization tools;
- the student is able to:
• decide on a suitable procedure based on the analyzed data and knowledge of visualization techniques,
• interpret the results achieved.
Course Contents
1) Introduction to visual analytics. Basic concepts.
2) Summary of acquired knowledge in the field of visualization.
3) Basic principles of interactive visualization.
4) Computational methods in visual analytics.
5) Visual analytics for data investigating and processing.
6) Visual analytics for understanding multivariate and graph data.
7) Visual analytics for understanding temporal and spatial data.
8) Visual analytics for understanding spatial events data
9) Visual analytics for understanding spatial time series
10) Visual analytics for understanding trajectories and mobility data
11) Visual analytics for understanding text, images and video.
12) Design, comparison and evaluation of visualization techniques.
13) Interacting with visualization.
14) Advanced concepts in visual analytics.
Recommended or Required Reading
Required Reading:
Andrienko N., Andrienko G., Fuchs G., Slingsby A., Turkay C., Wrobel S. Visual Analytics for Understanding Temporal Distributions and Variations. In: Visual Analytics for Data Scientists. Springer, Cham, 2020. https://doi.org/10.1007/978-3-030-56146-8_8
Munzner, T. Visualization Analysis and Design. A K Peters/CRC Press, 1 edition, 2014, ISBN 9781466508910.
Ward, M. O.,‎ Grinstein, G.,‎ Keim, D. Interactive Data Visualization: Foundations, Techniques, and Applications. A K Peters/CRC Press, Second Edition, 2015, ISBN 9781482257373.
Loth, A. Visual Analytics with Tableau, Wiley, 1st edition, 2019, ISBN: 9781119560203.
Andrienko N., Andrienko G., Fuchs G., Slingsby A., Turkay C., Wrobel S. Visual Analytics for Understanding Temporal Distributions and Variations. In: Visual Analytics for Data Scientists. Springer, Cham, 2020. https://doi.org/10.1007/978-3-030-56146-8_8
Munzner, T. Visualization Analysis and Design. A K Peters/CRC Press, 1 edition, 2014, ISBN 9781466508910.
Ward, M. O.,‎ Grinstein, G.,‎ Keim, D. Interactive Data Visualization: Foundations, Techniques, and Applications. A K Peters/CRC Press, Second Edition, 2015, ISBN 9781482257373.
Loth, A. Visual Analytics with Tableau, Wiley, 1st edition, 2019, ISBN: 9781119560203.
Recommended Reading:
Andrienko, N., Andrienko, A. Visual Analytics of Movement. Springer, ISBN 978-3642375828.
Andrienko, N., Andrienko, A. Exploratory Analysis of Spatial and Temporal Data. A Systematic Approach. Springer, 2006, ISBN 978-3-540-25994-7.
Keim, D., Kohlhammer, J., Ellis, G., Mansmann, F. Mastering the Information Age. Solving Problems with Visual Analytics. Eurographics Association, 2010, ISBN 978-3-905673-77-7.
Tominski, C., Schumann, H. Interactive Visual Data Analysis. A K Peters/CRC Press, 2020, ISBN 9780367898755.
Andrienko, N., Andrienko, A. Visual Analytics of Movement. Springer, ISBN 978-3642375828.
Andrienko, N., Andrienko, A. Exploratory Analysis of Spatial and Temporal Data. A Systematic Approach. Springer, 2006, ISBN 978-3-540-25994-7.
Keim, D., Kohlhammer, J., Ellis, G., Mansmann, F. Mastering the Information Age. Solving Problems with Visual Analytics. Eurographics Association, 2010, ISBN 978-3-905673-77-7.
Tominski, C., Schumann, H. Interactive Visual Data Analysis. A K Peters/CRC Press, 2020, ISBN 9780367898755.
Planned learning activities and teaching methods
Lectures, Tutorials
Assesment methods and criteria
Task TitleTask TypeMaximum Number of Points
(Act. for Subtasks)
Minimum Number of Points for Task Passing
Credit and ExaminationCredit and Examination100 (100)51
        CreditCredit33 17
        ExaminationExamination67 34