Automated Organization ProfileBrandenburg University of Technology (BTU)
Brandenburg University of Technology (BTU)
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: 150.0 (sum of 56 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
From an initial pool of 1,858 papers in Google Scholar (GS) and 418 papers in Web of Science (WoS), we screened the full texts of 500 papers between 2006 and 2025 and extracted data from 250 studies on both solar irradiance and PV output forecasting. The resulting database contains 5,277 observations across 11 variables, encompassing inputs, methodological, climatic, and contextual factors that differentiate forecast performance.The "r_subset_clean.csv" provides the database. The "LR_exported.Rmd" and the "mars_plots_all.Rmd" files provide the code to conduct the MARS and linear regressions on the data.
Authors
- Thi Ngoc Nguyen ;
- Felix Müsgens
From an initial pool of 1,858 papers in Google Scholar (GS) and 418 papers in Web of Science (WoS), we screened the full texts of 500 papers between 2006 and 2025 and extracted data from 250 studies on both solar irradiance and PV output forecasting. The resulting database contains 5,277 observations across 11 variables, encompassing inputs, methodological, climatic, and contextual factors that differentiate forecast performance.The "r_subset_clean.csv" provides the database. The "LR_exported.Rmd" and the "mars_plots_all.Rmd" files provide the code to conduct the MARS and linear regressions on the data.
Authors
- Thi Ngoc Nguyen ;
- Felix Müsgens
No description available
Authors
- Gram-Hanssen, Kirsten ;
- Jaeger-Erben, Melanie Gabriele
No description available
Authors
- Gram-Hanssen, Kirsten ;
- Jaeger-Erben, Melanie Gabriele
Supplementary Material 1
Authors
- He, Yangyang ;
- Houtenbos, Sanne ;
- Wippert, Pia-Maria
Supplementary Material 1
Authors
- He, Yangyang ;
- Houtenbos, Sanne ;
- Wippert, Pia-Maria
Supplementary Material 1.
Authors
- Bammert, Philip ;
- Schüttig, Wiebke ;
- Novelli, Anna ;
- Iashchenko, Iryna ;
- Spallek, Jacob ;
- Blume, Miriam ;
- Diehl, Katharina ;
- Moor, Irene ;
- Dragano, Nico ;
- Sundmacher, Leonie
Additional file 2: Table A1. List of reference hits used to set gene-specific bit score thresholds.
Authors
- Sidorczuk, Katarzyna ;
- Burdukiewicz, Michał ;
- Cerk, Klara ;
- Fritscher, Joachim ;
- Kingsley, Robert A. ;
- Schierack, Peter ;
- Hildebrand, Falk ;
- Kolenda, Rafał
Additional file 2: Table A1. List of reference hits used to set gene-specific bit score thresholds.
Authors
- Sidorczuk, Katarzyna ;
- Burdukiewicz, Michał ;
- Cerk, Klara ;
- Fritscher, Joachim ;
- Kingsley, Robert A. ;
- Schierack, Peter ;
- Hildebrand, Falk ;
- Kolenda, Rafał
Additional file 3: Table A2. Adhesin gene-specific bit score thresholds. These thresholds are used to determine gene presence absence in the strict version of the search.
Authors
- Sidorczuk, Katarzyna ;
- Burdukiewicz, Michał ;
- Cerk, Klara ;
- Fritscher, Joachim ;
- Kingsley, Robert A. ;
- Schierack, Peter ;
- Hildebrand, Falk ;
- Kolenda, Rafał