Automated Author ProfileHongwei Wang
Hongwei Wang
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: 4.9 (sum of 13 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Based on the carbon module of the improved InVEST model, the total carbon stock in Northeast China was estimated for the four time slots of the late 1980s, 2000, 2010 and 2020. The total carbon stock includes the aboveground biomass, belowground biomass, dead organic carbon, and soil organic carbon (0–30 cm in depth), with a spatial resolution of 100 m.
Authors
- Hongwei Wang
Based on the carbon module of the improved InVEST model, the total carbon stock in Northeast China was estimated for the four time slots of the late 1980s, 2000, 2010 and 2020. The total carbon stock includes the aboveground biomass, belowground biomass, dead organic carbon, and soil organic carbon (0–30 cm in depth), with a spatial resolution of 100 m.
Authors
- Hongwei Wang
On July 12, 2020, a Ms 5.1 moderate earthquake occurred on the north segment of the Tangshan fault in North China, which was the seismogenic fault of the 1976 Ms 7.8 Tangshan earthquake and numerous small-to-moderate earthquakes in recent decades in the Tangshan seismic zone. The Ms 5.1 event was well recorded by dense ground-motion observation stations, including the national strong-motion stations and seismic intensity stations. Totally, 242 three-component acceleration recordings were well processed and the ground motion intensity measures were calculated, including PGAs, PGVs, and 5%-damped PSAs.
Authors
- Hongwei Wang
This research data is longitudinal cross-sectional data that records the personal characteristics (including competence, benevolence, and integrity) and online reputation (platform’s online scoring and patients’ online reviews) of physicians on www.haodf.com.
Authors
- Yingli Gong ;
- Hongwei Wang ;
- Qiangwei Xia ;
- Lijuan Zheng ;
- Yunxiang Shi
This research data is longitudinal cross-sectional data that records the personal characteristics (including competence, benevolence, and integrity) and online reputation (platform’s online scoring and patients’ online reviews) of physicians on www.haodf.com.
Authors
- Yingli Gong ;
- Hongwei Wang ;
- Qiangwei Xia ;
- Lijuan Zheng ;
- Yunxiang Shi
This research data is longitudinal cross-sectional data that records the personal characteristics (including competence, benevolence, and integrity) and online reputation (platform’s online scoring and patients’ online reviews) of physicians on www.haodf.com.
Authors
- Yingli Gong ;
- Hongwei Wang ;
- Qiangwei Xia ;
- Lijuan Zheng ;
- Yunxiang Shi
S-wave spectra for spectral inversion analysis of the 2016-2017 central Italyseismicsequence.
Authors
- Hongwei Wang
Data used for spectra inversion of the 2016-2017 central Italy seismic sequence and propagation path attenuation curves, inverted source spectra, appraent source spectra, and the estimated source rupture parameters.
Authors
- Hongwei Wang
Data used for spectra inversion of the 2016-2017 central Italy seismic sequence and propagation path attenuation curves, inverted source spectra, appraent source spectra, and the estimated source rupture parameters.
Authors
- Hongwei Wang