Scientific Visualization (SciVis)5 ECTS
(englische Bezeichnung: Scientific Visualization)
(Prüfungsordnungsmodul: Scientific Visualization)

Lehrveranstaltungen:

• • Scientific Visualization
    (Vorlesung, 2 SWS, Tobias Günther, Di, 14:15 - 15:45, H4)
  • Tutorials to Scientific Visualization
    (Übung, 2 SWS, Tobias Günther et al., Do, 14:15 - 15:45, H4; Do, 10:15 - 11:45, Zoom-Meeting)

Empfohlene Voraussetzungen:

Es wird empfohlen, folgende Module zu absolvieren, bevor dieses Modul belegt wird:

Algorithmen und Datenstrukturen (WS 2021/2022)

Inhalt:

The amount of data, generated in the pursuit of scientific discovery, keeps rapidly increasing across all major scientific disciplines. How can we make sense of large, time-dependent, high-dimensional and multi-variate data? This lecture provides an introduction into scientific visualization. Throughout the course, we cover the fundamental perception basics needed to convey information accurately. After categorizing different data types based on their dimensionality, we dive deeper into specific techniques for scalar, vector and tensor valued data. To facilitate the discovery of patterns and to support the communication of findings, we further elaborate on data reduction, feature extraction, and interactive exploration.
The lecture covers the following topics:

• a review of scalar and vector calculus

• data structures and data types

• direct and indirect scalar field visualization

• geometry-based, feature-based and topology-based vector field visualization

• glyph-based tensor field visualization

• uncertainty and multi-variate data visualization

Lernziele und Kompetenzen:

Students are able to:

• classify data and select appropriate visualization techniques

• calculate differential properties of scalar and vector fields

• identify features in scalar and vector-valued data

• implement numerical extraction algorithms

• learn the advantages and disadvantages of common visualization techniques

• use perceptual basics to select appropriate visualization methods

• explain and apply common interaction and data exploration paradigms

Verwendbarkeit des Moduls / Einpassung in den Musterstudienplan:

1. International Information Systems (IIS) (Master of Science)
   (Po-Vers. 2021w | ReWiFak | International Information Systems (IIS) (Master of Science) | Gesamtkonto | Informatics | Data and knowledge - Informatics | Scientific Visualization)

Studien-/Prüfungsleistungen:

Scientific Visualization (Prüfungsnummer: 37221)

Prüfungsleistung, Klausur, Dauer (in Minuten): 90, benotet, 5 ECTS

Anteil an der Berechnung der Modulnote: 100.0 %

weitere Erläuterungen:
Klausur in elektronischer Form mit einem Anteil im Antwort-Wahl-Verfahren

Prüfungssprache: Englisch

Erstablegung: SS 2022, 1. Wdh.: WS 2022/2023

1. Prüfer:

Tobias Günther