Institute for Scientific Interchange FoundationGovernment

Italy

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Foundation: 1983

Mission: Information not localized

Vision: A tremendous flow of novel and quantitative social demographics and behavioral data allows us to move from the analysis of the “social atom” to the quantitative analysis of “social aggregate states”. A key factor in this shift of gear is to be found in the data revolution. The ISI has faced this new challenge by focusing on Data Science with the creation of specific labs and interdisciplinary research. Our research Labs are wired within the life of society and citizens. Society is an ever more entangled mixture of human beings and technologies, a chaotic reality of which we try to extract the underlying order to be able to make reliable predictions about its evolution and help decision makers and policy makers with realistic scenarios and models. With Data Science we want to recognize the picture that is hidden in the massive stream of data, to predict its occurrence in a statistical sense and control it. We use techniques borrowed from statistical physics, nonlinear dynamics, mathematics and computation theory. Our basic tools are sophisticated, innovative algorithms enabling us to discover hidden patterns of correlated information in large data sets. Our aim is to translate reality into the virtual universe.

NOTE: This institution is no longer available in Scimago Institutions Rankings

Evolution of the institution

The following data gives a quick reading on the scientific performance in the last years. The research ranking refers to the volume, impact and quality of the institution's research output. The innovation ranking is calculated on the number of patent applications of the institution and the citations that its research output receives from patents. Finally, the societal ranking is based on the number of pages of the institution's website and the number of backlinks and mentions from social networks.

Publishing profile

These are the journals used by the institution's researchers to publish their work in the last year. The size of each circle represents the value of the SJR of the publication, and its spatial position represents its subject matter.

This visualizatión allows you to identify the knowledge areas where the institution has published, recognize the prestige of the scientific journals in which the institution knowledge has been published, and identify predominant scientific communities.

Where is the institution located?

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