Automated Organization ProfileDepartment of Architecure, University of Roma Tre
Department of Architecure, University of Roma Tre
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets in this organization
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the organization's datasets
Total Mentions
Total mentions of the organization's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 2.0 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
The tool targets small municipalities in Europe. Through the award-winning certification system, the Protocol supports the fulfillment of best practices. Such practices can enhance town attractiveness to counteract excessive land use due to urban growth and to reduce demographic decline in internal areas. The research methodology is grounded on building a dynamic dataset using Geo Big Data, Local Data, Mobile Data (via ICT), and Real Time Data through sensors. This tool aims at building algorithms to calculate indicators measuring the quality standards of integrated interventions. The reason is to reach specific goals within the defined Priority Areas of the Historical Small Smart City. Being highly adaptive, the framework follows Urban Responsive Design principles based on weighted suitability models that can be calibrated by changing the input data and the weights of the linear combinations formula. The research results highlight varying framework data, including the tool’s development procedures and practicality.
Authors
- Pica, Valentina
The tool targets small municipalities in Europe. Through the award-winning certification system, the Protocol supports the fulfillment of best practices. Such practices can enhance town attractiveness to counteract excessive land use due to urban growth and to reduce demographic decline in internal areas. The research methodology is grounded on building a dynamic dataset using Geo Big Data, Local Data, Mobile Data (via ICT), and Real Time Data through sensors. This tool aims at building algorithms to calculate indicators measuring the quality standards of integrated interventions. The reason is to reach specific goals within the defined Priority Areas of the Historical Small Smart City. Being highly adaptive, the framework follows Urban Responsive Design principles based on weighted suitability models that can be calibrated by changing the input data and the weights of the linear combinations formula. The research results highlight varying framework data, including the tool’s development procedures and practicality.
Authors
- Pica, Valentina