Analysis method of scientific instrument data file format based on clustering idea

Jianhui Zhou; Feng Sun; Hao Shi; Shuai Shen

doi:10.1117/12.2653568

8 December 2022 Analysis method of scientific instrument data file format based on clustering idea

Jianhui Zhou, Feng Sun, Hao Shi, Shuai Shen

Proceedings Volume 12474, Second International Symposium on Computer Technology and Information Science (ISCTIS 2022); 124740J (2022) https://doi.org/10.1117/12.2653568
Event: Second International Symposium on Computer Technology and Information Science (ISCTIS 2022), 2022, Guilin, China

Abstract

Aiming at the problem of low analytical efficiency in the current analysis methods of data file format of scientific instruments, a data file format analysis method based on clustering was proposed to improve the efficiency of file format analysis. According to the file storage structure and the characteristics of cluster distribution, the selection principle of file samples in cluster analysis is formulated. At the same time, the corresponding format analysis auxiliary tool software is developed, which can automatically judge the rationality of the selected files and automatically group them, simplifying the corresponding format analysis process. The method and the developed tool are used to analyze the format of MS data generated by a mass spectrometry model. The experimental results show that the format of MS data obtained by this method is accurate and the efficiency is significantly improved. This method can effectively promote the sharing of data resources of large-scale scientific instruments and improve the utilization rate of data resources.

Citation Download Citation

Jianhui Zhou, Feng Sun, Hao Shi, and Shuai Shen "Analysis method of scientific instrument data file format based on clustering idea", Proc. SPIE 12474, Second International Symposium on Computer Technology and Information Science (ISCTIS 2022), 124740J (8 December 2022); https://doi.org/10.1117/12.2653568

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KEYWORDS

Data storage

Analytical research

Time metrology

Binary data

Data modeling

Data centers

Mechanical engineering

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