Data Processing and Visualization Techniques 2401-OG-EN-DPVT

Information visualization is the new interdisciplinary study of "the visual representation of large-scale collections of non-numerical information, such as files and lines of code in software systems, library and bibliographic databases, networks of relations on the internet, and so forth”. By using visual maps it is possible to study the structure and dynamics of the various fields of science and discover the scholar trends and themes.
While fields such as scientific visualization involve the presentation of data that has some physical or geometric correspondence, information visualization focuses on abstract data without such correspondences such as symbolic, tabular, networked, hierarchical, or textual information sources.
The course will highlight the process of producing effective visualizations that take the needs of users into account and illustrate practical visualization procedures. It will cover the
• history and related fields of information visualization
• perceptual basis of information visualization,
• major and advanced visualization techniques,
• data processing tools and techniques,
• discussions of information visualization systems and fundamental problems in the field.
The course objective is to give a practical knowledge of how to effectively visualize abstract information and hands-on experience in the application of this knowledge to specific domains, different tasks such as browsing or organizing information for diverse and possibly non-technical users.

Total student workload

Classes requiring direct participation of the teacher: lecture and workshop 25 hours (1 ECTS) Self-study: make up the series of homework according schedule of topics 25 hours (1 ECTS) Self-study: two final project preparation 50 hours (2 ECTS) Self-study: final project presentation and defense 25 hours (1 ECTS) Total: 125 h (5 ECTS)

Learning outcomes - knowledge

The students will have an elementary knowledge about visualisation technologies and basic terminology. The students will know modern methods for the visualisation of knowledge and large data.

Learning outcomes - skills

The students will be able to design complex visual layouts by selecting appropriate variables, labels and axes. The students will be able to visualize required announcement in both functional and aesthetic way.

Learning outcomes - social competencies

The students will be able to understand visual language of presented project, read it and correctly interpret as well as share their knowledge with other users regarding to their needs.

Teaching methods

- lecture - display - e-learning platform

Exploratory teaching methods

- laboratory
- project work

Prerequisites

The students be interested in data analysis and professional visualisation of data.

Assessment criteria

The final assessment include:
• regular attendance at lecture,
• make up the homework,
• 2 final projects design and presentation.
Evaluation scheme rely on following values: project’s substantive value (50%), mastery of technology (20%), aesthetic (10%), innovation (10%) and very essential optimizing output files (10%).

Practical placement

not applicable

Additional information

Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system:

Description of 2401-OG-EN-DPVT in USOSweb