Automated Author ProfileBithell, Sam
Durham University, United Kingdom
Bithell, Sam
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: 0.5 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Two survey areas were targetted using a Malå GeoScience Ramac X3M with a 500MHz antenna, and two further individual profiles were targetted using a PulseEkko Pro with a 200MHz antenna. Field 1 (see Figure 1) targetted the area indicated as containing the fort bath house (Taylor and Biggins, 2012). Poor data quality produced by the Malå in Field 1 was primarily as a result of uneven ground conditions and steep topography. Nonetheless, some linear and rectilinear features were identified, including overlying the indicative location of the fort bath house and previously unknown structures further to the south and on a different alignment. The PulseEkko was not deployed in Field 1 due to multiple overhead cables and a drystone wall which would have interfered the data due to the unshielded nature of the antennae. In Field 2 the data quality of the Malå is somewhat improved, due to better ground conditions and flatter topography. The PulseEkko was also deployed along two transects. Several features were identified using the Malå some of which are identifiable on the existing LiDAR. These features could be associated with either the Roman or Medieval occupation of the site; additional survey providing wider context would be necessary to make such distinctions. The PulseEkko was also deployed in Field 2 along two orthogonal lines. These surveys produced much higher data quality than the Malå and due to the lower frequency also provided greater depth penetration. The PulseEkko revealed evidence of several strong, laminated reflectors and multiple diffraction hyperbolae set in a complex stratigraphic sequence. The use of GPR at Bewcastle is confirmed as a productive method for future investigation of the Site with evidently conducive ground conditions. Preliminary survey has already identified several previously unknown features in both of the targetted fields, even in Field 1 where topography made the survey challenging. In addition to presentation of the results, some recommendations are made for future surveys which would mitigate some of the issues encountered during the pilot survey.
Authors
- Bithell, Sam