Automated Organization ProfileBiomedical Research Institute, Data Science Institute, University MS Center, UHasselt
Biomedical Research Institute, Data Science Institute, University MS Center, UHasselt
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: 4.0 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Multiple Sclerosis (MS) is an inflammatory autoimmune disease of the centralnervous system, causing increased vulnerability to infections and disabilityamong young adults. Ever since the coronavirus disease 2019 (COVID-19)outbreak, caused by severe acute respiratory syndrome coronavirus 2infections, there have been concerns among people with MS (PwMS) about thepotential interactions between various disease-modifying therapies andCOVID-19. The COVID-19 in MS Global Data Sharing Initiative (GDSI) wasinitiated in 2020 to address these concerns. This paper focuses on theanonymisation and open-sourcing of a GDSI sub-dataset, comprising data enteredby people with MS and clinicians using a fast data entry tool. The datasetincludes demographics, comorbidities, hospital stay, and COVID-19 symptoms ofPwMS. The dataset can be used to perform different statistical analyses toimprove our understanding of COVID-19 in MS. Furthermore, this dataset canalso be used within the context of educational activities to educate differentstakeholders on the complex data science topics that were used within theGDSI.
Authors
- Khan, Hamza ;
- Geys, Lotte ;
- baneke, peer ;
- Comi, Giancarlo ;
- Peeters, Liesbet
Multiple Sclerosis (MS) is an inflammatory autoimmune disease of the centralnervous system, causing increased vulnerability to infections and disabilityamong young adults. Ever since the coronavirus disease 2019 (COVID-19)outbreak, caused by severe acute respiratory syndrome coronavirus 2infections, there have been concerns among people with MS (PwMS) about thepotential interactions between various disease-modifying therapies andCOVID-19. The COVID-19 in MS Global Data Sharing Initiative (GDSI) wasinitiated in 2020 to address these concerns. This paper focuses on theanonymisation and open-sourcing of a GDSI sub-dataset, comprising data enteredby people with MS and clinicians using a fast data entry tool. The datasetincludes demographics, comorbidities, hospital stay, and COVID-19 symptoms ofPwMS. The dataset can be used to perform different statistical analyses toimprove our understanding of COVID-19 in MS. Furthermore, this dataset canalso be used within the context of educational activities to educate differentstakeholders on the complex data science topics that were used within theGDSI.
Authors
- Khan, Hamza ;
- Geys, Lotte ;
- baneke, peer ;
- Comi, Giancarlo ;
- Peeters, Liesbet