The amount of data and information collected and retained by organizations and businesses is constantly increasing, due to advances in data collection, computerization of transactions, and breakthroughs in storage technology. Further, many attributes are also recorded, resulting in very high-dimensional data sets. Typically, the applications involve large-scale information banks, such as data warehouses that contain interrelated data from a number of sources. Examples of new technologies giving rise to large, high-dimensional data sets are high-throughput genomic and proteomic technologies, sensor-based monitoring systems, etc. Finally, new application areas such as biochemical pathways, web documents, etc. produce data with inherent structure that cannot be simply captured by numbers.
CITATION STYLE
Michailidis, G. (2007). Data Visualization Through Their Graph Representations. In Handbook of Data Visualization (pp. 103–120). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-33037-0_5
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