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Embedding Analytics within the Curation of Scientific Workflows.

Gerard Weatherby¹, Michael R Gryk²

¹UCONN Health.

International Journal of Digital Curation

|March 26, 2021

Summary

This summary is machine-generated.

The National Center for Biomolecular NMR Data Processing and Analysis enhances data curation by embedding analytics into computational workflows and provenance tracking. This promotes reproducibility and data reuse among scientists.

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Area of Science:

Biomolecular NMR Spectroscopy
Computational Chemistry
Data Science

Background:

The National Center for Biomolecular NMR Data Processing and Analysis has developed computational workflow management software for NMR spectroscopists.
Previous work focused on refactoring the workflow system using the PREMIS framework for provenance and data sharing.
The goal was to support data reuse and improve the sharing of workflows.

Purpose of the Study:

To report on recent efforts to embed analytics within workflow execution and provenance tracking.
To enhance the curation practices of the National Center for Biomolecular NMR Data Processing and Analysis.
To foster computational reproducibility and scientific data reuse.

Main Methods:

Embedding analytics within workflow execution and provenance tracking.
Including important metrics for intermediate datasets within PREMIS intellectual objects.
Developing standalone metadata widgets for metric visualization.

Main Results:

Metrics for intermediate datasets are now part of PREMIS objects, allowing inspection and visualization of workflow changes.
The system supports both automated workflow execution and manual metadata management.
Domain experts are encouraged to be active data curators.

Conclusions:

The hybrid approach of automated workflows and manual metadata management fosters computational reproducibility.
Embedded analytics and metadata widgets facilitate scientific data reuse.
The developed system enhances the overall curation practices for biomolecular NMR data.