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Prototype of Kepler Processing Workflows For Microscopy And Neuroinformatics.

V Astakhov1, A Bandrowski2, A Gupta2

  • 1National Center for Microscopy Imaging Research, Basic Science Building 1000 University of California, San Diego 9500 Gilman Drive La Jolla, CA 92093-0608, USA.

Procedia Computer Science
|May 9, 2017
PubMed
Summary
This summary is machine-generated.

We developed a Kepler workflow engine for integrating microscope data from the National Center for Microscopy Imaging Research (NCMIR). This system enhances data sharing with projects like the Whole Brain Catalog (WBC) and Neuroscience Information Framework (NIF).

Keywords:
Data fusionKeplerMicroscopyNCMIRNIFNeuroinformaticsOntologyWeb ServicesWorkflow

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Area of Science:

  • Neuroscience
  • Bioinformatics
  • Data Science

Background:

  • The National Center for Microscopy Imaging Research (NCMIR) generates vast amounts of microscopy data.
  • Integrating and accessing this data across different neuroscience projects presents a significant challenge.

Purpose of the Study:

  • To prototype end-to-end application integration workflows for NCMIR microscope data using the Kepler workflow engine.
  • To facilitate data sharing and integration with external neuroscience initiatives.

Main Methods:

  • Utilized the Kepler workflow engine for application integration.
  • Leveraged the Cell Centered Database (CCDB) and integrated rule-oriented data system (IRODS) for data storage.
  • Developed specific workflows for data fusion and web service orchestration for the Neuroscience Information Framework (NIF).

Main Results:

  • Successfully prototyped end-to-end workflows for NCMIR data.
  • Integrated NCMIR data with external projects like the Whole Brain Catalog (WBC) and NIF.
  • Created a "Brain data flow" system for categorized access to brain region information.

Conclusions:

  • The Kepler workflow engine is effective for building integrated data pipelines in neuroscience research.
  • Enhanced data accessibility and interoperability for NCMIR data through integration with major neuroscience frameworks.
  • The developed system facilitates data fusion and web service orchestration, advancing neuroscience data sharing.