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Digital Humanities: Data Visualization

An introduction to digital humanities

Introduction

Data visualization is a broad term for using graphical presentation to represent quantitative data to provide the viewer with a qualitative understanding of information contents via visual insights. Scientific Visualization and Information Visualization are often considered subsets of Data Visualization.

Scientific Visualization

Scientific visualization "provides graphical representations of numerical data for their qualitative and quantitative analysis." (Hansen, & Johnson, 2011) It aims to improve interpretations of large data sets and to gain insights that may be overlooked by statistical methods. Scientific Visualization can be highly complex and specific to discipline. Examples include complex chemical hypothesis testing in laboratory, 3D modelling of human body for medical simulation, etc.

Information Visualization

Information visualization is a set of technologies that “use of computer-supported, interactive, visual representations of abstract data in order to amplify cognition" (Card, Mackinlay, & Shneiderman, 2009) It means that using graphical presentation and user interface for gaining knowledge about the structure of the data and relationships in it. Examples include graphs with statistical model, network analysis for social network data, and map representation with spatial data, etc.

Infographics 

Different from information visualization which create picture from a given set of data, Infographics means "a larger graphic design that combines data visualizations, illustrations, text, and images together into a format that tells a complete story" (Krum, 2013) which "gain direct attention, guide view transitions, and orient the user via visual narrative tactics". (Segel and Heer, 2010)

Visual Analytics

Visual analytics is the science of analytical reasoning supported by interactive visual interfaces. (Keim et al. , 2009). The goal of visual analytics research is thus to turn the information overload into an opportunity which allows decision makers to combine their flexibility, creativity, and background knowledge with the enormous storage and processing capacities of today’s computers to gain insight into complex problems.

References

Hansen, C. D., & Johnson, C. R. (2011). Visualization handbook. Elsevier.

Keim, D. A., Mansmann, F., Stoffel, A., & Ziegler, H. (2009). Visual Analytics. Encyclopedia of Database Systems, 3341–3346. https://doi.org/10.1007/978-0-387-39940-9_1122

‌Card, S., Mackinlay, J. D., & Shneiderman, B. (2009). Information visualization. Human-computer interaction: Design issues, solutions, and applications181.

Segel, E., & Heer, J. (2010). Narrative visualization: Telling stories with data. IEEE transactions on visualization and computer graphics16(6), 1139-1148.

Krum, R. (2013). Cool infographics: Effective communication with data visualization and design. John Wiley & Sons.

Digital Scholarship Librarian

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Terry Chung
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