Overview
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ABSTRACT
Activity logs of actors and organizations in the socio-economic sphere are now the focus of various analytical devices to measure trends or predict future directions. Interpreting patterns emerging from the mining of the data still remains a matter of human intelligence: judging the relevance of a result, appraising the meaning and potential impact, and if necessary making the right decisions. Information visualization turns patterns into visual structure, and relies on our ability to easily process graphical information. The challenge is therefore to provide a well-designed map of the data, and give users the power to interact and access the underlying data easily.
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Guy MELANÇON: CNRS UMR 5800 LaBRI and Université de Bordeaux
INTRODUCTION
Any activity carried out today – by companies, organizations or institutions – is synonymous with the production or collection of data to keep a record of this activity or those involved in it. The world of research is developing methods to make the most of this data, to mine, analyze and model it. The monitoring activity, which combines data collection and analysis, is at the heart of a process that enables socio-economic players to constantly adjust their position and strategy in relation to their environment.
The data collected and stored in this way is often complex, as are the phenomena from which it is derived, but also often because it is unstructured. Data mining algorithms are used to extract structural patterns or association rules from the data, the first form of knowledge gained from the data. Companies are interested in drawing up profiles of their customers to better target their sales campaigns, for example; observers of public debate will want to identify the players determining the barycentres of opinions. Because data is massive and complex, the results of data mining are often just as complex. These results need to be sorted and classified to arrive at a useful synthesis for decision-making, or to formulate an explanatory hypothesis for the phenomenon under study.
The success of the excavation operation depends on the ability to read the patterns discovered. The interpretation of these patterns, the evaluation of their relevance and the applicative potential of the results of the search remain a very human affair, the complexity and subtlety of which cannot today be entrusted to an automaton. In the end, only humans can judge the relevance of a result, appreciate its meaning and potential impact, and make the right decisions where necessary.
The field of information visualization is based on a fundamental observation: around 20% of our brain activity is devoted to processing visual signals . The challenge is therefore to offer the user a mapping of data that enables him or her, on the one hand, to visually identify the patterns that have become graphical, and on the other, to act on the visualization to access the underlying data or modify the representation in order to understand the structure that is...
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KEYWORDS
multidimensional projection | similarity computation | graph drawing | data analysis | exploratory statistics | data exploration | information maps
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Bibliography
Websites
GapMinder (Hans Rosling) – A fact-based worldview http://www.gapminder.org
Patrick Healey website http://www.csc.ncsu.edu/faculty/healey/PP/
Color Brewer http://www.colorbrewer2.org/
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