Ricardo Cunha | Scientific Researcher
Institut für Umwelt & Energie, Technik & Analytik e. V. (IUTA)

Ricardo Cunha, Scientific Researcher, Institut für Umwelt & Energie, Technik & Analytik e. V. (IUTA)

I am a researcher active in the fileds of data science, analytical chemistry, environmental technology and biological engennering. Currently, I am part of the StreamFind (https://github.com/odea-project/StreamFind) develop team. Also, I am involved/manage projects within the mentioned research areas.


Day 1 (26th June) @ 15:15

Harmonizing data with an open-source approach and interoperable format

In response to the escalating complexity of instrumental analysis data, current processing solutions, such as monolithic software and microservices, face challenges in user adoption. Non-target screening (NTS) for environmental analysis faces additional challenges, as proprietary software lacks flexibility for diverse use cases. The StreamFind platform addresses these challenges by integrating open source software for data processing. Developed as an R library with a microservices architecture, StreamFind aims to enhance users' data literacy by providing a flexible and understandable solution for assembling data processing workflows. Core components, such as MassSpecData and RamanData, are specifically designed for mass spectrometry and Raman data, utilizing open source tools and native algorithms for efficient data processing. Central to StreamFind is the ProcessingSettings class, ensuring harmonization of processing methods for consistency and reproducibility. A demonstration of the StreamFind library showcases its capabilities, featuring an NTS workflow applied to mass spectrometry data from wastewater treatment. The StreamFind structure facilitates user-friendly scripting and automation, enabling command line deployment for reproducibility and data sharing. Future development will focus on enhancing processing capabilities with advanced and open source algorithms, and expanding processing engines to accommodate various data types. This approach aims to support interdisciplinary studies. The StreamFind R library is available for installation from the ODEA project's GitHub repository (https://github.com/odea-project/StreamFind), accompanied by comprehensive documentation, tutorials, and examples. Collaborative contributions to the project and the integration of additional open source tools are encouraged, fostering a collective effort towards advancing environmental data processing.

last published: 17/Apr/24 08:15 GMT

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