Encouraging data citation and discovery with the Data Citation Index

Area of Science:

• Scholarly communication
• Bibliometrics
• Data management

Background:

• Researchers desire increased attribution for non-traditional scholarly output.
• Existing systems often lack robust data citation mechanisms.
• The need for better data discovery and synthesis is growing.

Purpose of the Study:

• To provide an overview of the Data Citation Index.
• To explain its role in linking research articles to datasets.
• To highlight its function in tracking and encouraging data citation.

Main Methods:

• The Data Citation Index was launched on the Web of Science platform.
• It evaluates data repositories based on relevance to scientific research.
• It facilitates cross-disciplinary search capabilities for data discovery.

Main Results:

• The Index links published research to underlying data sets.
• It tracks the citation of data, promoting author credit.
• It enables new possibilities for data discovery and synthesis.

Conclusions:

• The Data Citation Index addresses the need for data attribution and reuse.
• It supports the formalization and adoption of data citation standards.
• It fosters a climate of increased credit for data contributions in research.