Automated Author ProfileLi, Nan
Tsinghua University School of Environment
Li, Nan
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: 2.8 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This dataset has been established to address the lack of a comprehensive lifecycle inventory dataset for China's aluminum industry, a sector of critical importance due to its environmental and economic implications. It comprises 38 data sources, 216 processes and 2193 flows of China’s aluminum industry. The data collection process was rigorously conducted, adhering to the rules of data traceability and transparency. This dataset contributes significantly to the aluminum sector in China, enhancing the accuracy of LCA studies and supporting more informed and sustainable decisions.
Authors
- Xie, Jinliang ;
- Feng, Yuzhen ;
- Chang, Huimin ;
- Xu, Changqing ;
- Xiong, Ruoxi ;
- Cai, Zimeng ;
- Fu, Chenling ;
- Xia, Ziqian ;
- Guo, Jing ;
- Li, Nan
This dataset has been established to address the lack of a comprehensive lifecycle inventory dataset for China's aluminum industry, a sector of critical importance due to its environmental and economic implications. It comprises 38 data sources, 216 processes and 2193 flows of China’s aluminum industry. The data collection process was rigorously conducted, adhering to the rules of data traceability and transparency. This dataset contributes significantly to the aluminum sector in China, enhancing the accuracy of LCA studies and supporting more informed and sustainable decisions.
Authors
- Xie, Jinliang ;
- Feng, Yuzhen ;
- Chang, Huimin ;
- Xu, Changqing ;
- Xiong, Ruoxi ;
- Cai, Zimeng ;
- Fu, Chenling ;
- Xia, Ziqian ;
- Guo, Jing ;
- Li, Nan