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FAIR data sharing is labor-intensive. This talk illustrates how ChatGPT can help us. The presentation consists of part 1 "Fair FAIR Intro", part 2 "Free ChatGPT", part 3 "Paid ChatGPT+: FAIR GPT", and conclusions. Part 1 provides a fair introduction into the FAIR data sharing and ends up with a description of a FAIR research process. Part 2 describes functionalities of free ChatGPT in the area of FAIR data sharing. Part 3 introduces a FAIR GPT within ChatGPT+, a virtual FAIR data consultant taking knowledge from the external APIs and uploaded files to reduce hallucinations. FAIR GPT: https://chat.openai.com/g/g-BkMR28wlV-fairFAIR GPT documentation at GitHub: https://github.com/UB-Mannheim/FAIR-GPT
FAIR data, ChatGPT, FAIR principles, FAIR
FAIR data, ChatGPT, FAIR principles, FAIR
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |