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DVID: Distributed Versioned Image-Oriented Dataservice.

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  • 1Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, United States.

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|February 27, 2019
PubMed
Summary
This summary is machine-generated.

The DVID system offers a distributed versioning approach for electron microscopy (EM) connectomics datasets, enabling collaborative data modification and integration similar to code repositories. This open-source software facilitates efficient data management and reconstruction workflows.

Keywords:
EM reconstructionbig datacollaborationconnectomicsdataservicedatastoredistributed version controlversioning

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Area of Science:

  • Neuroscience
  • Computer Science
  • Data Management

Background:

  • Open-source software development, exemplified by platforms like GitHub, has enabled collaborative code sharing and version control.
  • The increasing scale of electron microscopy (EM) datasets in connectomics presents challenges for data sharing and collaborative modification.
  • Existing data publication methods for EM datasets lack mechanisms for flexible data branching and reintegration.

Purpose of the Study:

  • To introduce the DVID system as a distributed versioning approach for EM-based connectomics datasets.
  • To provide a web-based API for managing and accessing connectomics data.
  • To support collaborative reconstruction workflows and data-driven experiments.

Main Methods:

  • Development of the DVID (Distributed Data Versioning) system, a web-based API for connectomics data.
  • Implementation of distributed versioning concepts within reconstruction workflows.
  • Integration of DVID with various storage systems, including local SSDs and cloud object stores.
  • Tailoring backend storage to specific connectomics data types for optimized performance.

Main Results:

  • DVID enables branched and versioned data, supporting proofreader training and segmentation experiments.
  • The system facilitates flexible data modification and reintegration through moderated acceptance of changes.
  • DVID supports deployment on diverse hardware, from laptops to large servers, with efficient storage and fast queries.
  • The system is available as open-source software with growing storage support.

Conclusions:

  • DVID provides a novel distributed versioning system for EM connectomics data, addressing challenges in collaborative research.
  • The system enhances data management, workflow efficiency, and collaborative capabilities within the connectomics community.
  • DVID's open-source nature and flexible deployment options promote wider adoption and advancement in neuroinformatics.