Automated Author Profile
Parker, Douglas
University of Leeds
0000-0003-2335-8198

Current S-Index

2.6

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

1.3

Average Dataset Index per dataset

Total Datasets

Total datasets for this author

Average FAIR Score

67.3%

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: 2.6 (sum of 2 datasets Dataset Index scores)

More information here.

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

GCRF African SWIFT Skills Matrix for Professionals in the Field of African Meteorology

The Skill Framework is for two purposes:1. It will be used to monitor the success of the SWIFT project, in supporting the increase of skills (capability) among the body of staff working on the project.2. It should be used by participants to plan their own personal development. You may consider taking account of this Skills Framework in your staff review process, for instance.SWIFT participants should record their skills levels in the "Personal" sheet, and use this to plan their personal development in the project. Each participant should keep their own copy of the spreadsheet, and share a copy with their line manager. Participants will be asked to send a copy of the spreadsheet to the SWIFT Programme Science Director at ACMAD. The data will be anonymised and used to monitor progress.

Authors

Parker, Douglas

1 Citation0 Mentions77% FAIR2.0 Dataset Index

10.5518/1003January 2021

CSU AMMA/NAMMA Sounding Data. Version 1.0 (Version: 1.0)

This dataset contains the quality-controlled soundings from the NASA African Monsoon Multidisciplinary Analyses (NAMMA/AMMA) project collected from 31 May to 6 Nov 2006. The data are contained in one TAR/GNU Zip file, which also contains a FORTRAN program for reading the upper-air sounding data files. Please see the provided readme file for more information.