1/1
FAIR Video Case Study: Haiping Lu - PyKale - Accessible machine learning from multiple sources for interdisciplinary research
Version 2 2022-08-30, 09:09
Version 1 2022-08-25, 13:51
media
posted on 2022-08-30, 09:09 authored by Sort Of... Films, Haiping LuHaiping Lu, Jenni AdamsJenni Adams
A video case study in which Dr Haiping Lu discusses his application of the FAIR data and software principles to his research on accessible and sustainable machine learning.
FAIR refers to the principles applied to make research data and software findable, accessible, interoperable and reusable.
Filmed and produced by Sort Of... Films in May-July 2022. Interview conducted by Jenni Adams (University of Sheffield Library)
The file UoS_FAIR_Haiping_Lu_FINALCUT contains the video itself, while the file UoS_FAIR_Haiping_Lu_FINALCUT.mp4.srt contains the subtitles.
History
Ethics
- There is no personal data or any that requires ethical approval
Policy
- The data complies with the institution and funders' policies on access and sharing
Sharing and access restrictions
- The data can be shared openly
Data description
- The file formats are open or commonly used
Methodology, headings and units
- Headings and units are explained in the files
