S-index: Adapting Bibliometric Principles to Measure and Incentivize Data Sharing
Data sharing is fundamental for transparency, reproducibility, and accelerating scientific discovery. Currently there is no widely available or accepted metric to evaluate the extent and utility of data sharing. The proposed bibliometric-based S-index aims to address this gap by adapting the conceptual principles of established bibliometrics, specifically drawing inspiration from the h-index and complementary g-index, and applying them directly to the evaluation of data sharing and reuse. The feasibility of this approach is demonstrated with a LLM-based classification of extant literature.
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The proposed S-index has the potential for significant impact by directly encouraging and recognizing data sharing efforts. By providing a quantifiable measure of a dataset's impact and utility, it offers a new form of academic credit for researchers who invest time and resources in curating and sharing their data.
