Automated Author ProfileBertoni, Eleonora
Joint Research Centre0000-0002-2063-4022
Bertoni, Eleonora
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: 0.9 (sum of 3 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This dataset maps the competences of the European Digital Competence Framework (DigComp) to the skills descriptors in ESCO, the European classification of skills, qualifications and occupations, which is the target classification used in Skills-OVATE, a database of European online job advertisements (OJA). This experimental mapping allows to reconcile the “demand side” of digital skills sought by employers with the “supply side” of education and training for digital skills, through the lens of DigComp, which is used in many EU digital skills initiatives at international, national and regional levels.
Authors
- Sostero, Matteo ;
- Cosgrove, Judith ;
- Bertoni, Eleonora
This dataset maps the competences of the European Digital Competence Framework (DigComp) to the skills descriptors in ESCO, the European classification of skills, qualifications and occupations, which is the target classification used in Skills-OVATE, a database of European online job advertisements (OJA). This experimental mapping allows to reconcile the “demand side” of digital skills sought by employers with the “supply side” of education and training for digital skills, through the lens of DigComp, which is used in many EU digital skills initiatives at international, national and regional levels.
Authors
- Sostero, Matteo ;
- Cosgrove, Judith ;
- Bertoni, Eleonora
This dataset maps the competences of the European Digital Competence Framework (DigComp) to the skills descriptors in ESCO, the European classification of skills, qualifications and occupations, which is the target classification used in Skills-OVATE, a database of European online job advertisements (OJA). This experimental mapping allows to reconcile the “demand side” of digital skills sought by employers with the “supply side” of education and training for digital skills, through the lens of DigComp, which is used in many EU digital skills initiatives at international, national and regional levels.
Authors
- Sostero, Matteo ;
- Cosgrove, Judith ;
- Bertoni, Eleonora