Researchers have developed a new indicator using large language models (LLMs) to measure the reuse of research data in scholarly publications. This AI-driven approach revealed a data reuse rate of 43%, surpassing traditional bibliometric methods. The findings suggest that the positive impacts of research data sharing and reuse may be currently underestimated, and that LLMs can effectively measure these effects at scale. AI
IMPACT Provides a scalable method to quantify the impact of open science practices, potentially influencing future research evaluation and funding.
RANK_REASON Academic paper detailing a new methodology for measuring research data reuse using LLMs.
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