The FOSSR-RISIS Data Science School Tools and Methods for Analysing Complex Science, Technology, and Innovation (STI) Systems, will take place online from February 24th to 27th, 2025.
In the framework the NRRP project FOSSR and the RISIS infrastructure, the school offers an in-depth exploration of advanced statistical techniques and methodologies to analyze STI systems. Participants will engage with topics such as Network Models, Bayesian Networks, Machine Learning, and Spatial Models, with a balance between theory and application.
Key topics include:
- Network Science (NS): Analysis of the structure and dynamics of complex systems in Science, Technology, and Innovation (STI).
- Bayesian Networks (BN): Probabilistic models and inference methods applied to understand dependencies among variables.
- Machine Learning (ML): Tools for identifying key factors and enabling classification in model-free scenarios.
- Spatial Models (SM): Techniques for analyzing geographical patterns and distributions in STI systems.
The school includes practical exercises using R and real-world datasets, allowing participants to apply learned concepts. Sessions will be held in English, and accessibility measures will ensure inclusivity for participants from diverse backgrounds.
Application Details
Deadline: January 30, 2025
Notification of acceptance: February 7, 2025
Participation is limited to 40 attendees, selected based on the relevance of their CVs to the course topics.
For more details and registration
This Winter School supports the integration of advanced data analysis techniques into Open Science frameworks, fostering data-driven decision-making in STI research.
