Automated Author ProfileAlcamo, Joseph
Alcamo, Joseph
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: 1.3 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
The attached table contains source information and measured concentrations of faecal coliform bacteria (FC), biochemical oxygen demand (BOD), and total dissolved solids (TDS). These measurements come from published literature and constitute supplementary information for the manuscript mentioned in the reference (in this context, the data was used for model validation and testing). This dataset was used for the project "The world's water quality: A pre-study for a worldwide assessment" for which funding was provided by the United Nations Environmental Programme (UNEP) and UN-Water.
Authors
- Rivera, Jaime ;
- Alcamo, Joseph ;
- Flörke, Martina ;
- Reder, Klara ;
- Bärlund, Ilona ;
- Kynast, Ellen ;
- Malsy, Marcus ;
- Borchardt, Dietrich
These datasets contain modeled monthly mean loadings and concentrations of faecal coliform bacteria (FC), biochemical oxygen demand (BOD), and total dissolved solids (TDS) in river networks of Asia, Africa, and Latin America for the periods 1990-1992 and 2008-2010. These loadings and concentrations were estimated with WorldQual (part of the WaterGAP3 modeling framework) on a 5 arc-min resolution grid. These datasets were elaborated as part of the project “The world's water quality: A pre-study for a worldwide assessment” for which funding was provided by the United Nations Environmental Programme (UNEP) and UN-Water. The datasets are supplementary for the manuscript mentioned in the reference.
Authors
- Alcamo, Joseph ;
- Flörke, Martina ;
- Reder, Klara ;
- Bärlund, Ilona ;
- Kynasst, Ellen ;
- Borchardt, Dietrich ;
- Malsy, Marcus ;
- Rivera, Jaime