Full Paper

FAIR Principle:Make the Multimodal Data in Science & Technology Linkage Research Reliable

Chai Miaoling ORCID,Zhang Xian ORCID

DOI: 10.23106/dcmi.952401345

Abstract

The research uses the FAIR principle from the perspective of libraries to construct a reliable data selection and evaluation model for the study of the relationship between science and technology, in order to solve the problems of insufficient utilization of other data and unclear application logic, which mainly rely on paper and patent data in current research. Three issues are discussing in the paper: the format and interaction methods of multimodal data, the construction of indicator system, and the evaluation process. The result shows that the index construction method based on metadata interoperability is beneficial for the fusion of metadata layer, and use ontology to achieve semantic fusion, and identified scientific and technological relationships by multimodal data jointly.

Author information

Chai Miaoling

1. National Science Library (Chengdu), Chinese Academy of Sciences, China;2. Department of Information Resources Management, School of Economics and Management, University of Chinese Academy of Sciences, China,CN

Zhang Xian

1. National Science Library (Chengdu), Chinese Academy of Sciences, China;2. Department of Information Resources Management, School of Economics and Management, University of Chinese Academy of Sciences, China,CN

Cite this article

Miaoling, C., & Xian, Z. (2024). FAIR Principle:Make the Multimodal Data in Science & Technology Linkage Research Reliable. Proceedings of the International Conference on Dublin Core and Metadata Applications, 2024. https://doi.org/10.23106/dcmi.952401345
Published

Issue

DCMI-2024 Toronto, Canada Proceedings
Location:
University of Toronto, Toronto, Ontario, Canada
Dates:
October 20-23, 2024
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