Wolfgang Aigner is the scientific director at the Institute of Creative\Media/Technologies at the St. Pölten University of Applied Sciences, Austria and adjunct professor at TU Wien, Austria. In 2013, he received his habilitation in computer science for his work on "Interactive Visualization and Data Analysis: Visual Analytics with a Focus on Time" from TU Wien. From 2006 to 2010, he was deputy head of the Department of Information and Knowledge Engineering at Danube University Krems, Austria and from 2010 to 2013, he was deputy head of the Laura Bassi Centre of Expertise for Visual Analytics Science and Technology (CVAST) at TU Wien, Austria. Dr. Aigner is an expert in information visualization and visual analytics, particularly in the context of time-oriented data, where he has authored and co-authored more than 140 scientific publications. He served as program committee member and chair for various scientific conferences and acts as associate editor for scientific journals. He has received national awards for his research work, was awarded a Top Cited Article 2005-2010 from Pergamon/Elsevier, and received a best paper honorable mention at the IEEE Conference on Visual Analytics Science and Technology (VAST). Since 2002, Wolfgang has been involved in the acquisition and execution of a number of funded basic and applied research projects at the national and international levels.

Silvia Miksch is a university professor and head of the research division "Visual Analytics" (CVAST), Institute of Visual Computing and Human-Centered Technology, TU Wien since 2015. She has been head of the Information and Knowledge Engineering research group, Institute of Software Technology & Interactive Systems, TU Wien from 1998 to 2015. From 2006 to 2010 she was university professor and head of the Department of Information and Knowledge Engineering (ike) at Danube University Krems, Austria. In April 2010 she established the awarded Laura Bassi Centre of Expertise for Visual Analytics Science and Technology (CVAST) funded by the Federal Ministry of Economy, Family and Youth of the Republic of Austria. Silvia has acquired, led, and has been involved in several national and international applied and basic research projects. She served as paper co-chair of several conferences including IEEE VAST 2010, 2011, and 2020 and overall papers chair IEEE VIS 2021 as well as EuroVis 2012, and on the editorial board of several journals including IEEE TVCG and CGF. She acts on various strategic committees, such as the VAST and EuroVis steering committees as well as the VIS executive committee. In 2020 she was inducted into the IEEE Visualization Academy. Furthermore, she acts as scientific reporter in the board of the Austrian Research Fund (FwF) and is advisory board member of the Vienna Science and Technology Fund (WWTF). She has more than 300 scientific publications and her main research interests are visualization and visual analytics over time and space with particular focus on interaction techniques, network-based, knowledge-assisted, and guidance-enriched methods.

Heidrun Schumann is a professor emeritus at the University of Rostock, Germany, where she was heading the Chair of Computer Graphics at the Institute for Visual & Analytic Computing. She received doctoral degree (Dr.-Ing.) in 1981 and post-doctoral degree (Dr.-Ing. habil.) in 1989. Her research and teaching activities cover a variety of topics related to computer graphics, including information visualization, visual analytics, and rendering. She is interested in visualizing complex data in space and time, combining visualization and terrain rendering, and facilitating visual data analysis with progressive methods. A key focus of Heidrun's work is to intertwine visual, analytic, and interactive methods for making sense of data. Heidrun published more than two hundred articles in top venues and journals. She co-authored the first German textbook on data visualization in 2000 and a textbook s

Ausführlich mit anschaulichen Beispielen stellt das Buch die Grundlagen der Visualisierung und den Visualisierungsprozeß dar. Die Autoren beschreiben detailliert die visuellen Variablen Position und Größe, Farbe und Textur, Form und Tiefe sowie Bewegung. Ebenfalls vorgestellt werden Konzepte zur Visualisierung spezieller Datenklassen, insbesondere die Visualisierung von Multiparameterdatensätzen. Bei der Visualisierung von Volumendaten, die z.B. bei medizinischen und technischen Anwendungen anfallen, stehen praktische Aspekte im Vordergrund.

1 Anforderungen an eine Visualisierung.- 1.1 Ziel der Visualisierung.- 1.2 Allgemeine Anforderungen.- 1.3 Expressivität.- 1.4 Effektivität.- 1.5 Angemessenheit.- 1.6 Zusammenfassung.- 2 Der Visualisierungsprozeß.- 2.1 Die Visualisierungspipeline.- 2.2 Referenzmodell für die Visualisierung.- 2.3 Visualisierungsszenarien.- 2.4 Zusammenfassung.- 3 Beschreibung der Daten als Ausgangspunkt einer Visualisierung.- 3.1 Datenquellen.- 3.2 Der Beobachtungsraum.- 3.3 Die Merkmale.- 3.4 Die Datenmenge.- 3.5 Ansätze zur Datenspezifikation.- 3.6 Datenformate.- 3.7 Reduktion einer Datenmenge.- 3.8 Anmerkungen und Probleme.- 3.9 Zusammenfassung.- 4 Einflußfaktoren auf die Visualisierung.- 4.1 Bearbeitungsziele.- 4.2 Wahrnehmungskapazitäten und Präferenzen des Anwenders.- 4.3 Anwendungsumgebung und Ressourcen.- 4.4 Zusammenfassung.- 5 Grundlegende Techniken.- 5.1 Methodik der Abbildung.- 5.2 Abbildung auf Position, Größe und Orientierung.- 5.3 Abbildung auf Struktur und Form.- 5.4 Abbildung auf Farbe.- 5.5 Abbildung auf Textur.- 5.6 Zusammenfassung.- 6 Visualisierung von Multiparameterdaten in Raum und Zeit.- 6.1 Begriffsklärung und Entwicklungen.- 6.2 Visualisierung multivariater Daten.- 6.3 Berücksichtigung der mehrdimensionalen Daten.- 6.4 Zusammenfassung.- 7 Visualisierung von Volumendaten.- 7.1 Begriffsklärung.- 7.2 Grundlegende Schritte der Volumenvisualisierung.- 7.3 Methoden der Volumenvisualisierung.- 7.4 Weiterführende Konzepte.- 7.5 Zusammenfassung.- 8 Visualisierung von Strömungsdaten.- 8.1 Problembeschreibung und Begriffsklärung.- 8.2 Visualisierungspipeline für Strömungsdaten.- 8.3 Methoden der Strömungsvisualisierung.- 8.4 Zusammenfassung.- 9 Zusammenfassung und Ausblick.- 9.1 Weiterführende Konzepte.- 9.2 Visualisierungssysteme.- 9.3 Anwendungen.-Literatur.