FAIR GPT: A virtual consultant for research data management in ChatGPT

Autor:	Shigapov, Renat, Schumm, Irene
Rok vydání:	2024
Předmět:	Computer Science - Digital Libraries Computer Science - Artificial Intelligence Computer Science - Information Retrieval
Druh dokumentu:	Working Paper
Popis:	FAIR GPT is a first virtual consultant in ChatGPT designed to help researchers and organizations make their data and metadata compliant with the FAIR (Findable, Accessible, Interoperable, Reusable) principles. It provides guidance on metadata improvement, dataset organization, and repository selection. To ensure accuracy, FAIR GPT uses external APIs to assess dataset FAIRness, retrieve controlled vocabularies, and recommend repositories, minimizing hallucination and improving precision. It also assists in creating documentation (data and software management plans, README files, and codebooks), and selecting proper licenses. This paper describes its features, applications, and limitations. Comment: 4 pages, 2 figures, 1 table
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2410.07108 Zobrazit plný text záznamu View this record from Arxiv