Perspectives and Good Practices in Visualization of Knowledge About Public Entities

Perspectives and Good Practices in Visualization of Knowledge About Public Entities

Jan Fazlagić (Poznan University of Economics and Business, Poland), Windham Loopesko (University of Colorado – Denver, USA), Leszek Matuszak (Poznan University of Economics and Business, Poland) and Rigby Johnson (University of Colorado – Denver, USA)
DOI: 10.4018/978-1-5225-4990-1.ch011

Abstract

Visualization of knowledge in public entities is becoming more and more popular due to the development of information technology tools, the demand for solutions allowing for reduction of information overload (IO), and new approaches to local government, including citizen participation. The chapter presents some case study examples of knowledge visualization in public entities with some conclusions and recommendations for policy makers. Additionally, it presents a complete map of certain Polish counties prepared by the authors. The authors applied, apart from the visualization in the form a map, the “Chernoff Faces” method (invented by Herman Chernoff in 1973). This method displays multivariate data on Polish counties in the shape of a human face. The individual parts, such as eyes, ears, mouth, and nose, represent values of the variables by their shape, size, placement, and orientation. The idea behind using faces is that humans easily recognize faces and notice small changes without difficulty. Chernoff Faces handle each variable differently.
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Knowledge Visualization Vs. Information Visualization

Knowledge visualization and information visualization are related techniques, as they both assist in visualizing different abstraction levels of data (Burkhard, 2005). Robert Meyer distinguishes among:

  • Data, which are symbols or facts that are isolated and have not yet been interpreted;

  • Information

. . . is more sophisticated. It is data that has been interpreted or processed and therefore contains some meaning and can give answers to questions like ‘who?’, ‘what?’, ‘where?’, ‘why?’ or ‘when?’ For those who do not comprehend the meaning it still stays data.

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