Frontiers of Data and Domputing ›› 2022, Vol. 4 ›› Issue (1): 69-83.doi: 10.11871/jfdc.issn.2096-742X.2022.01.006

• Special Issue: Union of National Scientific Data Center • Previous Articles     Next Articles

Research on Interoperability Models between Scientific Data Centers

LU Yihang1,2(),LI Guoqing1,3(),CHEN Zugang1,3,*()   

  1. 1. Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
    2. The University of Chinese Academy of Sciences, Beijing 100049, China
    3. China National Earth Observation Data Center, Beijing 100094, China
  • Received:2021-10-07 Online:2022-02-20 Published:2022-03-04
  • Contact: CHEN Zugang E-mail:luyihang20@mails.ucas.ac.cn;ligq@aircas.ac.cn;chenzg@aircas.ac.cn

Abstract:

[Objective] This paper aims to meet the need for data interoperability in cross-disciplinary scientific research, to solve the problem of duplication of data resource storage, and to promote the effective use of interdisciplinary data resources. [Methods] This paper investigates the existing scientific data interoperability technologies and models and the current status of interoperability between scientific data centers at home and abroad. The characteristics of China’s scientific data centers and the applicable conditions of various interoperable models and technologies are analyzed. [Results] Seven interoperability models are proposed, including the switching-across model based on metadata harvesting, the metadata registry model based on the metadata framework, the Linked Data model based on Multi-domain ontology mapping, the metadata mapping model, the ontology-based model, the existing system re-integration model and the unified information system model. Additionally, we provide recommendations for implementing the interoperability model of the scientific data centers in our country. [Conclusions] The interoperability models between scientific data centers proposed in this study are implementable, which can greatly promote the data sharing and utilization of cross-disciplinary scientific data resources and have great significance and value.

Key words: scientific data interoperability, scientific data center, interoperability model, metadata, mappings, controlled vocabularies