Data has been increasingly recognized as a critical factor in the future economy. However,
constructing an efficient data trading market faces challenges such as privacy breaches …

Vertical Federated Learning (VFL) has emerged as a popular machine learning paradigm,
enabling model training across the data and the task parties with different features about the …

With the prevalence of data-driven intelligence, data markets with various data products are
gaining considerable interest as a promising paradigm for commoditizing data and …

In the digital era, data has become a pivotal asset, advancing technologies such as
autonomous driving. Despite this, data trading faces challenges like the absence of robust …

With the rising awareness of data assets, data governance, which is to understand where
data comes from, how it is collected, and how it is used, has been assuming evergrowing …

Abstract Artificial Intelligence (AI) and IT governance are playing an increasingly significant
role in managing industrial pollution in Canada. With the nation's commitment to reducing …

Background Multicenter clinical research faces many challenges, including how to
quantitatively evaluate the data contribution of each research center. However, few data …

Public-facing data-driven technologies such as social media platforms and search engines
rely on data producers, such as users and crowd workers, to be feasible and financially …

With the advancement of the digital strategic transformation of power enterprise, how to
efficiently use massive smart grid data to serve society and benefit enterprises has become …

Data elements, as a new type of production factor, have begun to be integrated into the
national economic value creation system. Data assetization is an important way to realize …