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Research Infrastructure for Science and Innovation Studies Research Infrastructure for Science and Innovation Studies
  • About RISIS
    • Description
    • Objectives
    • Documentation
    • Blog / News
  • Members
    • Partners
    • People
    • Governing Board
    • Committees
  • Resources
    • Datasets
    • Organisation Registers
    • Indicators
    • Services
    • Methods for data analysis
  • Training
    • Methodological courses
    • Summer Schools
    • Methods in Action
  • Seminars
    • Research Seminars
    • Policymakers Sessions
  • Outputs
    • Zenodo
    • Policy briefs
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Archives

Tag Archives for: "STI communities"
FOSSR-RISIS Data Science Winter School on Tools and methods for analysing complex Science, Technology and Innovation (STI) systems
0
By Serena Fabrizio
In
Posted February 24, 2025

FOSSR-RISIS Data Science Winter School on Tools and methods for analysing complex Science, Technology and Innovation (STI) systems

The FOSSR-RISIS Data Science Winter School on Tools and methods for analysing complex Science is organized by the Research Institute of  Sustainable Economic Growth (CNR-IRCrES) in the framework [...]

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RISIS Data Science Winter School on Tools and methods for analysing complex Science, Technology and Innovation (STI) systems
0
By Serena Fabrizio
In
Posted February 20, 2023

RISIS Data Science Winter School on Tools and methods for analysing complex Science, Technology and Innovation (STI) systems

The RISIS Data Science Winter School on Tools and methods for analysing complex Science, Technology and Innovation (STI) systems: A gentle introduction to Network Science (NS), Spatial Models [...]

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RISIS Data Science Winter School: 25 selected of more than 150 applications
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By Serena Fabrizio
In Blog, news
Posted January 12, 2023

RISIS Data Science Winter School: 25 selected of more than 150 applications

More than 150 requests of participation reached RISIS Data Science Winter School Secretariat during this very successful edition. Only 25 participants coming from various countries were admitted [...]

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This project is funded by the European Union under Horizon2020 Research and Innovation Programme Grant Agreement n°82409

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