A safe and intelligent experimental data management system and method

Abstract

The invention provides a safe and intelligent experimental data management system and method. The invention includes: a research sub-center data management subsystem, a data resource center subsystem, a safety control subsystem, a data intelligent analysis subsystem, a data visualization subsystem, a user management subsystem, and a data verification subsystem. Through the one-button installation and data upload function, the present invention greatly reduces the burden of installation and upload for scientific research personnel, and classifies and stores chemical and physical experiment results in different formats from different research sub-centers through the data resource center subsystem , broaden the diversity of the data storage system, facilitate the visual inspection of categories in the future data verification process, and effectively ensure the authenticity and reliability of the experimental data through the security control subsystems set up on the network, operating system and application side , greatly reducing the possibility of academic fraud. The invention can be widely popularized in the technical field of experimental data management.

Description

technical field [0001] The present invention relates to the technical field of experimental data management, in particular to a safe and intelligent experimental data management system and method. Background technique [0002] Experimental data is an important supporting material for scientific research results, and its reusable nature makes it even more valuable in the long run than the scientific research results generated by the data. The two major categories of chemistry and physics are experimental disciplines with large data output , which has many subdisciplines. Due to the different research directions under each subdiscipline, the format of the experimental data produced is completely different. Experimental data formats are not limited to basic data formats, but also include special formats generated by various chemical analysis software or physical modeling software. This makes it difficult to store the experimental data generated by chemistry and physics in the ...

AI Technical Summary

Problems solved by technology

There are many problems in the existing experimental data management software. First, the data diversification storage capacity is insufficient. The existing experimental data management software can only process the experimental data obtained by more conventional software with suffixes such as jpg, dwg, and cgr in the experimental process. data, while the experimental data obtained by Scatt, NG, POLYRATE, Molpro, Amber, and Turbomole software with more complex data cannot be well compatible or expanded, making conventional software laborious in the process of developing these functions; second, security Performance considerations are not in place, and only the security of the network side or the application side is guaranteed. Although the basic security of the data is guaranteed, it still cannot guarantee that the administrator or a higher-level manager can modify the experimental data in the data operating system. Tampering with the experimental data to ensure that the data conforms to the standards, and not paying attention to the authenticity of the experimental data has also caused serious problems in the academic integrity of some of our scientific research laboratories in the world, seriously affecting our country's reputation in the world academic field. Credibility, plagiarism in the field of physical modeling also occurs from time to time. When students graduate / researchers leave their jobs, it is difficult to check the original actual situation, which also causes troubles for schools / research institutions / enterprises; third, function Complicated, cumbersome steps in installation or use, failed to consider the real working conditions of the experimenters, some chemical and physical experimental data calculation process and the conclusions obtained at each step are quite huge, which also makes it difficult to upload experimental data when uploading It takes a long time, and the existing technology needs to be constantly paid attention to when uploading, otherwise data will be lost or incomplete, and researchers will also spend time and energy

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