Automated Organization ProfileTechnische Universität Wien Fakultät für Technische Chemie
Technische Universität Wien Fakultät für Technische Chemie
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: 3.3 (sum of 4 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This record contains a docker image for data evaluation of AFM-IR data for our publication 'Understanding the resolution and sensitivity in photothermal nanoscale chemical imaging - a point spread function approach'. The evaluations can be accessed by running the container and accessing the contained Jupyter Lab via a browser. The calculations are contained in 'Figure preparations.ipynb'.To run the container (requires docker):1.download 'container.tar.gz'2. in the command line, execute 'docker load -i pillars.tar.gz'. This will return something like 'Loaded image: '3. then 'docker run -p 8888:8888 pillars:latest jupyter notebook --ip 0.0.0.0 --NotebookApp.default_url=/lab --port 8888'4.In your command line a link starting in 'http://127.0.0.1:8888/lab?token=...' will appear. Open this link in your browser to access the evaluation In addition to running the container, files can be accessed directly in the files.zip folder. The contens of this folder are described in README.txt.
Authors
- Zhang, Yide ;
- Yilmaz, Ufuk ;
- Vorobev, Artem S. ;
- Iadanza, Simone ;
- O'Faolain, Liam ;
- Lendl, Bernhard ;
- Ramer, Georg
This record contains a docker image for data evaluation of AFM-IR data for our publication 'Understanding the resolution and sensitivity in photothermal nanoscale chemical imaging - a point spread function approach'. The evaluations can be accessed by running the container and accessing the contained Jupyter Lab via a browser. The calculations are contained in 'Figure preparations.ipynb'.To run the container (requires docker):1.download 'container.tar.gz'2. in the command line, execute 'docker load -i pillars.tar.gz'. This will return something like 'Loaded image: '3. then 'docker run -p 8888:8888 pillars:latest jupyter notebook --ip 0.0.0.0 --NotebookApp.default_url=/lab --port 8888'4.In your command line a link starting in 'http://127.0.0.1:8888/lab?token=...' will appear. Open this link in your browser to access the evaluation In addition to running the container, files can be accessed directly in the files.zip folder. The contens of this folder are described in README.txt.
Authors
- Zhang, Yide ;
- Yilmaz, Ufuk ;
- Vorobev, Artem S. ;
- Iadanza, Simone ;
- O'Faolain, Liam ;
- Lendl, Bernhard ;
- Ramer, Georg
This record contains a docker container image of the data evaluation shown in the publication "External cavity quantum cascade laser vibrational circular dichroism spectroscopy for fast and sensitive analysis of proteins at low concentrations". The evaluations can be accessed by running the container and accessing the contained Jupyter Lab via a browser. The calculations are contained in 'Eval_protein_D2O.ipynb'.To run the container (requires docker):1.download 'd2o_vcd.tar'2. in the command line, execute 'docker load -i d2o_vcd.tar'. This will return something like 'Loaded image: ' with image_name probably being "drhermann/vcd_d2o_00:trial_03"3. then 'docker run -p 8889:8889 ' replacing the brackets with the actual name of the image, such as drhermann/vcd_d2o_00:trial_034.In your command line a link starting in 'http://127.0.0.1:8888/lab?token=...' will appear. Open this link in your browser to access the evaluation.
Authors
- Hermann, Daniel-Ralph ;
- Ramer, Georg ;
- Lendl, Bernhard
This record contains a docker container image of the data evaluation shown in the publication "External cavity quantum cascade laser vibrational circular dichroism spectroscopy for fast and sensitive analysis of proteins at low concentrations". The evaluations can be accessed by running the container and accessing the contained Jupyter Lab via a browser. The calculations are contained in 'Eval_protein_D2O.ipynb'.To run the container (requires docker):1.download 'd2o_vcd.tar'2. in the command line, execute 'docker load -i d2o_vcd.tar'. This will return something like 'Loaded image: ' with image_name probably being "drhermann/vcd_d2o_00:trial_03"3. then 'docker run -p 8889:8889 ' replacing the brackets with the actual name of the image, such as drhermann/vcd_d2o_00:trial_034.In your command line a link starting in 'http://127.0.0.1:8888/lab?token=...' will appear. Open this link in your browser to access the evaluation.
Authors
- Hermann, Daniel-Ralph ;
- Ramer, Georg ;
- Lendl, Bernhard