Titel: | Exploration und Implementierung von Visualisierungstechniken für Covid-19-Daten | Sprache: | Englisch | Autorenschaft: | Chau Vu, Thi Ngan | Schlagwörter: | Visualization; Data; Covid-19; Visualization Fundamentals; Visualization Principles; Design Process; Visualization Evaluation | Erscheinungsdatum: | 28-Feb-2024 | Zusammenfassung: | Visualization techniques have played a prominent role in conveying scientific information about COVID-19 to a broad audience, including policymakers, scientists, healthcare providers, and the general public. The main objective of this thesis is to explore the application of data visualization techniques in analyzing and effectively communicating the impact of the COVID-19 pandemic. The research starts by establishing the fundamentals of data visualization, which include essential terminologies, concepts, and general data visualization principles. The upcoming chapters will illustrate the process of designing data visualizations, emphasizing the various stages required to produce impactful visual representations. Further, the thesis explores different methodologies for data visualization and presents a methodological framework and a guide for information visualization techniques. Through a case study employing an exploratory data analysis approach, this thesis demonstrates implementing and evaluating data visualizations in COVID-19 analysis. The evaluation aims to determine how compelling the visualizations are in conveying information and facilitating data exploration. This thesis enhances our comprehension of the potential of data visualization in conveying and comprehending the complicated consequences of the COVID-19 pandemic. |
URI: | http://hdl.handle.net/20.500.12738/14933 | Einrichtung: | Department Informatik Fakultät Technik und Informatik |
Dokumenttyp: | Abschlussarbeit | Abschlussarbeitentyp: | Bachelorarbeit | Hauptgutachter*in: | Tropmann-Frick, Marina | Gutachter*in der Arbeit: | Sarstedt, Stefan |
Enthalten in den Sammlungen: | Theses |
Dateien zu dieser Ressource:
Datei | Beschreibung | Größe | Format | |
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Exploration_and_Implementation_of_Data_Visualisation_on_Covid_19_Data_geschwärzt.pdf | 4.42 MB | Adobe PDF | Öffnen/Anzeigen |
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