Automated Author ProfileRiascos Goyes, Juan Fernando
Riascos Goyes, Juan Fernando
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author'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: 0.6 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This item is part of a study on the relationship between urban morphology and human mobility using graph-theoretical and statistical methods. The research involves a comparative classification of built environments in nine U.S. metropolitan areas based on density, connectivity, and spatial structure. The materials uploaded here include [figures/maps/data/code] supporting the identification of morphological patterns and their link to mobility indicators such as public transport use and car dependence. These results contribute to a reproducible framework for integrating spatial typologies into urban mobility analysis and planning.
Authors
- Riascos Goyes, Juan Fernando ;
- Guarin-Zapata, Nicolas ;
- Ospina Zapata, Juan Pablo ;
- Lowry, Michael
This item is part of a study on the relationship between urban morphology and human mobility using graph-theoretical and statistical methods. The research involves a comparative classification of built environments in nine U.S. metropolitan areas based on density, connectivity, and spatial structure. The materials uploaded here include [figures/maps/data/code] supporting the identification of morphological patterns and their link to mobility indicators such as public transport use and car dependence. These results contribute to a reproducible framework for integrating spatial typologies into urban mobility analysis and planning.
Authors
- Riascos Goyes, Juan Fernando ;
- Guarin-Zapata, Nicolas ;
- Ospina Zapata, Juan Pablo ;
- Lowry, Michael