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ARTICLE
Integrated Sharing Platform for Genetic Data of Rare and Precious Metal Materials
1 School of Information Science and Engineering, Yunnan University, Kunming, 650500, China
2 Yunnan Provincial Academy of Science and Technology, Kunming, 650028, China
* Corresponding Author: Jingjing Yang. Email:
Computers, Materials & Continua 2025, 85(3), 4587-4606. https://doi.org/10.32604/cmc.2025.068370
Received 27 May 2025; Accepted 28 August 2025; Issue published 23 October 2025
Abstract
The construction of centralized and standardized material databases is essential to support both scientific innovation and industrial application. However, for rare and precious metal materials, existing data resources are often decentralized. This results in persistent issues such as data silos and fragmentation, which significantly hinder efficient data utilization and collaboration. In response to these challenges, this study investigates the development of an integrated platform for sharing genetic data of rare and precious metal materials. The research begins by analyzing current trends in material data platforms, both domestically and internationally. These insights help inform the architectural design. The core of the platform consists of several key modules. Data resource integration is designed to aggregate and harmonize heterogeneous data from diverse sources. A structured data management system supports efficient storage and retrieval. A computational environment enables data analysis and modeling. A trusted sharing mechanism ensures security and access control. By integrating these functionalities, the platform aims to provide a unified ecosystem. This system facilitates open yet secure data exchange, promotes reproducibility, and enhances research efficiency. Finally, the article summarizes the initial implementation of the platform. It discusses its potential limitations and outlines future directions for development, including the integration of artificial intelligence tools and the expansion of data coverage.Keywords
Cite This Article
Copyright © 2025 The Author(s). Published by Tech Science Press.This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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