Enhancing data management in E-government using data categorization and visualization techniques

Abstract

Modern information and communication systems can process massive amounts of data automatically and efficiently, but human beings have a limited cognitive capacity. Organizations that handle data on a larger scale need to adjust and streamline their operations in order to cope with this complexity. The e-Government information systems present problems that are on an entirely different scale, with communication streams between citizens and government easily dwarfing those in the private sectors. The information flows in e-Government are further constrained by established processes and practices that are hard to change and strict privacy concerns. A solution to problems of complexity and inefficiency of data manipulation in e-Government is needed. This chapter analyzes models and techniques of data categorization and visualization that can be employed in the context of e-Government. Methods of categorization, metadata, and ontologies in particular are explored for use in such an environment. A simple government ontology framework is developed as a starting point for introduction of ontologies into the e-Government context and the information is structured in such a way to allow easy correlation and navigation between concepts. A simple but intuitive visual representation of information and their relations is developed to facilitate better understanding of complex topics.