data analysis

Abstract: Science monitoring is a core issue in the new world of business and research. Companies and institutes need to monitor the activities of their competitors, get information on the market, changing technologies or government policies. This paper presents the Tétralogie platform that is aimed at allowing a user to interactively discover trends in scientific research and communities from large textual collections that include information about geographical location. Tétralogie consists of several agents that communicate with each other on users’ demands in order to deliver results to them. Metadata and document content are extracted before being mined. Results are displayed in the form of histograms, networks and geographical maps; these complementary types of presentations increase the possibilities of analysis compared to the use of these tools separately. We illustrate the overall process through a case study of scientific literature analysis and show how the different agents can be combined to discover the structure of a domain. The system correctly predicts the country contribution to a field in future years and allows exploration of the relationships between countries.

 Information Visualization;  knowledge discovery;  information mining;  data analysis;  Domain knowledge;  Geographical maps;  

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Abstract: Extensible scientific visualization tools are often offered as data analysis tools. While images may be the goal of visualization, insight is the goal of analysis. Visualization tools often fail to reflect this fact both in functionality and in their user interfaces, which typically focus on graphics and programming concepts rather than on concepts more meaningful to end-user scientists. This paper presents a characterization which shows how data visualization fits into the broader process of scientific data analysis. We conducted an empirical study, observing scientists from several disciplines while they analyzed their own data. Examination of the observations exposed process elements outside conventional image viewing. For example, analysts queried for quantitative information, made a variety of comparisons, applied math, managed data, and kept records. The characterization of scientific data analysis reveals activity beyond that traditionally supported by computer. It offers an understanding which has the potential to be applied to many future designs, and suggests specific recommendations for improving the support of this important aspect of scientific computing

 Visualization Taxonomy;  data visualisation;  data visualization;  data analysis;  image viewing;  quantitative information;  scientific computing;  scientific data analysis process;  

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