DecentralDC: Assessing data contribution under decentralized sharing and exchange blockchain.

ABSTRACT: The issue of data quality has emerged as a critical concern, as low-quality data can impede data sharing, diminish intrinsic value, and result in economic losses. Current research on data quality assessment primarily focuses on four dimensions: intrinsic, contextual, presentational, and accessibility quality, with intrinsic and presentational quality mainly centered on data content, and contextual quality reflecting data usage scenarios. However, existing approaches lack consideration for the behavior of data within specific application scenarios, which encompasses the degree of participation and support of data within a given scenario, offering valuable insights for optimizing resource deployment and business processes. In response, this paper proposes a data contribution assessment metho

SUBMITTER: Ke W 

PROVIDER: S-EPMC11500924 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature