  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.
