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Related Experiment Video

Updated: May 13, 2026

Clean Sampling and Analysis of River and Estuarine Waters for Trace Metal Studies
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Published on: July 1, 2016

Data Science Orchestrator: A Containerized Trusted Research Environment for Flexible and Secure Analytical Pipelines.

Jori Kern1,2,3,4,5,6, Markus Brechtel7,8, Philipp Kaluza9

  • 1Federated Information Systems, German Cancer Research Center (DKFZ), Heidelberg, Germany.

Studies in Health Technology and Informatics
|May 17, 2025
PubMed
Summary

The Data Science Orchestrator (DSO) enhances research reproducibility and data security by providing a turnkey solution for deploying analysis tools. It also supports federated analysis and automated reporting pipelines for broader research infrastructure needs.

Keywords:
Data ProcessingSoftware DevelopmentTrusted Research Environment

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Area of Science:

  • Data Science
  • Computational Research
  • Research Infrastructure

Background:

  • Researchers often use personal laptops with non-versioned datasets and unvetted software, risking data leaks and hindering result reproducibility.
  • Current practices for data analysis are often slow, tedious, and lack robust security and version control.

Purpose of the Study:

  • To introduce the Data Science Orchestrator (DSO) as a solution for secure and reproducible data analysis.
  • To expand the DSO's capabilities to address broader research infrastructure needs beyond initial data analysis.

Main Methods:

  • Development of the Data Science Orchestrator (DSO) as a turnkey solution for deploying analysis tools.
  • Analysis of researcher requirements to identify needs for federated analysis and automated reporting pipelines.
  • Implementation of automated analysis pipelines for repeated reporting at different intervals.

Main Results:

  • The DSO provides a secure and reproducible environment for data analysis.
  • The DSO's scope has been expanded to include federated data analysis capabilities.
  • Automated analysis pipelines enable repeated reporting and extend the DSO's impact.

Conclusions:

  • The Data Science Orchestrator significantly improves research safety, reproducibility, and efficiency.
  • The expanded DSO addresses critical research infrastructure needs, supporting advanced data analysis and reporting.