In the present academic landscape, the process of collecting data is slow, and the lax infrastructures for data collaborations lead to significant delays in coming up with and disseminating conclusive findings. Therefore, there is an increasing need for a secure, scalable, and trustworthy data-sharing ecosystem that promotes and rewards collaborative data-sharing efforts among researchers, and a robust incentive mechanism is required to achieve this objective. Reputation-based incentives, such as the h-index, have historically played a pivotal role in the academic community. However, the h-index suffers from several limitations. This paper introduces the SCIENCE-index, a blockchain-based metric measuring a researcher's scientific contributions. Utilizing the Microsoft Academic Graph and machine learning techniques, the SCIENCE-index predicts the progress made by a researcher over their career and provides a soft incentive for sharing their datasets with peer researchers. To incentivize researchers to share their data, the SCIENCE-index is augmented to include a data-sharing parameter. DataCite, a database of openly available datasets, proxies this parameter, which is further enhanced by including a researcher's data-sharing activity. Our model is evaluated by comparing the distribution of its output for geographically diverse researchers to that of the h-index. We observe that it results in a much more even spread of evaluations. The SCIENCE-index is a crucial component in constructing a decentralized protocol that promotes trust-based data sharing, addressing the current inequity in dataset sharing. The work outlined in this paper provides the foundation for assessing scientific contributions in future data-sharing spaces powered by decentralized applications.

翻译：在当前的学术环境中，数据收集过程缓慢，而数据协作的基础设施薄弱，导致得出并传播确凿结论的工作出现严重延迟。因此，迫切需要建立一个安全、可扩展且可信赖的数据共享生态系统，以促进并奖励研究者之间的协作式数据共享努力，而实现这一目标需要强大的激励机制。历史上，基于声誉的激励机制（如h指数）在学术界发挥了关键作用。然而，h指数存在若干局限性。本文介绍了SCIENCE指数，这是一种基于区块链的度量指标，用于衡量研究者的科学贡献。利用微软学术图谱与机器学习技术，SCIENCE指数预测研究者职业生涯中所取得的进展，并为其与同行研究者共享数据集提供软激励。为鼓励研究者共享数据，SCIENCE指数被扩展以包含数据共享参数。该参数通过开放可用数据集数据库DataCite进行代理，并进一步纳入研究者的数据共享活动以增强其效能。我们通过将模型输出在不同地理区域研究者中的分布与h指数分布进行比较来评估模型。我们观察到，该模型得出的评价分布更为均匀。SCIENCE指数是构建促进基于信任的数据共享的去中心化协议的关键组成部分，旨在解决当前数据集共享中的不平等问题。本文所述工作为未来由去中心化应用驱动的数据共享空间中评估科学贡献奠定了基础。