Automated Author ProfileThoms, Lars-Jochen
Thurgau University of Teacher EducationUniversity of Konstanz0000-0002-2855-6153
Thoms, Lars-Jochen
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: 6.2 (sum of 6 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This dataset contains the results of a quantitative online survey (n = 67) conducted in 2025 as part of the OrChemSTAR project. The survey evaluated a web-based open-source tool that automatically converts SMILES notation into 3D molecular structures for use in chemistry education. Data were collected with a standardized questionnaire based on the Technology Acceptance Model (TAM), measuring perceived ease of use, perceived usefulness, and behavioral intention to use. The sample included diverse user groups such as teachers, students, and researchers. The dataset comprises responses to individual items, demographic information, and derived scale scores.
Authors
- Thoms, Lars-Jochen
This dataset contains the results of a quantitative online survey (n = 67) conducted in 2025 as part of the OrChemSTAR project. The survey evaluated a web-based open-source tool that automatically converts SMILES notation into 3D molecular structures for use in chemistry education. Data were collected with a standardized questionnaire based on the Technology Acceptance Model (TAM), measuring perceived ease of use, perceived usefulness, and behavioral intention to use. The sample included diverse user groups such as teachers, students, and researchers. The dataset comprises responses to individual items, demographic information, and derived scale scores.
Authors
- Thoms, Lars-Jochen
This dataset comprises 7909 hand-drawn chemical structure elements captured during field testing of the OrChemSTAR App in chemistry classes. It includes raw images as well as images with an overlay of recognized molecule parts based on 18 different classes relevant to chemical structure interpretation. The Annotations were done by the Structure Matching and Recognition Engine SMARE.
Authors
- Thoms, Lars-Jochen
This dataset comprises 7909 hand-drawn chemical structure elements captured during field testing of the OrChemSTAR App in chemistry classes. It includes raw images as well as images with an overlay of recognized molecule parts based on 18 different classes relevant to chemical structure interpretation. The Annotations were done by the Structure Matching and Recognition Engine SMARE.
Authors
- Thoms, Lars-Jochen
This dataset comprises 1844 hand-drawn chemical structure elements used to train and evaluate the SMARE (Structure Matching and Recognition Engine) model. It includes images annotated with 18 different classes relevant to chemical structure interpretation.
Authors
- Thoms, Lars-Jochen ;
- Rothlin, Tobias
This dataset comprises 1844 hand-drawn chemical structure elements used to train and evaluate the SMARE (Structure Matching and Recognition Engine) model. It includes images annotated with 18 different classes relevant to chemical structure interpretation.
Authors
- Thoms, Lars-Jochen ;
- Rothlin, Tobias