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Other literature type . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Presentation . 2024
License: CC BY
Data sources: Datacite
ZENODO
Presentation . 2024
License: CC BY
Data sources: Datacite
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FAIR Use of GPT-Generated Data in SSH Research: A Practical Guide

descriptionPublicationkeyboard_double_arrow_right Presentation , Other literature type 21 Aug 2024 English Publisher:Zenodo
Authors: Hindermann, Maximilian;

doi: 10.5281/zenodo.13939596 , 10.5281/zenodo.13939595

FAIR Use of GPT-Generated Data in SSH Research: A Practical Guide

Abstract

Over the past year, the Research and Infrastructure Support (RISE) team at the University of Basel has been exploring the use of Generative Pre-trained Transformers (GPTs) in the field of Social Sciences and Humanities (SSH). One of the main challenges we encountered was to make GPT-generated data FAIR (Findable, Accessible, Interoperable and Re-usable). In this talk, RISE member Maximilian Hindermann will share key learnings and practical tips his team has gathered. 

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Keywords

LLM, data, GPT, SSH, FAIR

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selected citations
These citations are derived from selected sources.
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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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