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Published on: November 8, 2019
A novel storage method for near infrared spectroscopy chemometric models
Zhi-Min Zhang1, Shan Chen, Yi-Zeng Liang
1College of Chemistry and Chemical Engineering, Research Center of Modernization of Chinese Medicines, Central South University, Changsha 410083, PR China.
Analytica Chimica Acta
|May 25, 2010
Summary
Chemometric Modeling Markup Language (CMML) solves chemometrics model sharing issues by storing models in XML documents. This enables easier data reuse across software and programming languages.
Area of Science:
- Chemometrics
- Data Science
- Spectroscopy
Background:
- Sharing chemometrics models faces interoperability challenges.
- Binary data formats hinder model reuse across different software.
- Standardized methods for model storage and exchange are needed.
Purpose of the Study:
- Introduce Chemometric Modeling Markup Language (CMML) for unified chemometrics model storage.
- Address the interoperability issue in sharing chemometrics models.
- Facilitate model reuse across diverse software and programming languages.
Main Methods:
- Developed CMML based on Extensible Markup Language (XML) principles.
- Utilized base64 encode/decode algorithms to convert binary data to strings.
- Implemented CMML storage for sampling, variable selection, preprocessing, outlier, and modeling parameters.
Main Results:
- CMML enables storing complete chemometrics models within a single XML document.
- Base64 encoding balances usability and file size for model data.
- CMML facilitates easy model reuse in various software via XML parsing.
- XPath allows effective data selection within CMML files.
Conclusions:
- CMML provides a robust solution for chemometrics model interoperability.
- The XML-based structure ensures broad compatibility and reusability.
- Open-source implementation in C++ demonstrates practical application, with ongoing development for MATLAB and R.
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