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DVID: Distributed Versioned Image-Oriented Dataservice
Open-source software development has skyrocketed in part due to community tools like github.com, which allows publication of code as well as the ability to create branches and push accepted modifications back to the original repository. As the number and size of EM-based datasets increases, the conn...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371063/ https://www.ncbi.nlm.nih.gov/pubmed/30804760 http://dx.doi.org/10.3389/fncir.2019.00005 |
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author | Katz, William T. Plaza, Stephen M. |
author_facet | Katz, William T. Plaza, Stephen M. |
author_sort | Katz, William T. |
collection | PubMed |
description | Open-source software development has skyrocketed in part due to community tools like github.com, which allows publication of code as well as the ability to create branches and push accepted modifications back to the original repository. As the number and size of EM-based datasets increases, the connectomics community faces similar issues when we publish snapshot data corresponding to a publication. Ideally, there would be a mechanism where remote collaborators could modify branches of the data and then flexibly reintegrate results via moderated acceptance of changes. The DVID system provides a web-based connectomics API and the first steps toward such a distributed versioning approach to EM-based connectomics datasets. Through its use as the central data resource for Janelia's FlyEM team, we have integrated the concepts of distributed versioning into reconstruction workflows, allowing support for proofreader training and segmentation experiments through branched, versioned data. DVID also supports persistence to a variety of storage systems from high-speed local SSDs to cloud-based object stores, which allows its deployment on laptops as well as large servers. The tailoring of the backend storage to each type of connectomics data leads to efficient storage and fast queries. DVID is freely available as open-source software with an increasing number of supported storage options. |
format | Online Article Text |
id | pubmed-6371063 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-63710632019-02-25 DVID: Distributed Versioned Image-Oriented Dataservice Katz, William T. Plaza, Stephen M. Front Neural Circuits Neuroscience Open-source software development has skyrocketed in part due to community tools like github.com, which allows publication of code as well as the ability to create branches and push accepted modifications back to the original repository. As the number and size of EM-based datasets increases, the connectomics community faces similar issues when we publish snapshot data corresponding to a publication. Ideally, there would be a mechanism where remote collaborators could modify branches of the data and then flexibly reintegrate results via moderated acceptance of changes. The DVID system provides a web-based connectomics API and the first steps toward such a distributed versioning approach to EM-based connectomics datasets. Through its use as the central data resource for Janelia's FlyEM team, we have integrated the concepts of distributed versioning into reconstruction workflows, allowing support for proofreader training and segmentation experiments through branched, versioned data. DVID also supports persistence to a variety of storage systems from high-speed local SSDs to cloud-based object stores, which allows its deployment on laptops as well as large servers. The tailoring of the backend storage to each type of connectomics data leads to efficient storage and fast queries. DVID is freely available as open-source software with an increasing number of supported storage options. Frontiers Media S.A. 2019-02-05 /pmc/articles/PMC6371063/ /pubmed/30804760 http://dx.doi.org/10.3389/fncir.2019.00005 Text en Copyright © 2019 Katz and Plaza. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Katz, William T. Plaza, Stephen M. DVID: Distributed Versioned Image-Oriented Dataservice |
title | DVID: Distributed Versioned Image-Oriented Dataservice |
title_full | DVID: Distributed Versioned Image-Oriented Dataservice |
title_fullStr | DVID: Distributed Versioned Image-Oriented Dataservice |
title_full_unstemmed | DVID: Distributed Versioned Image-Oriented Dataservice |
title_short | DVID: Distributed Versioned Image-Oriented Dataservice |
title_sort | dvid: distributed versioned image-oriented dataservice |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371063/ https://www.ncbi.nlm.nih.gov/pubmed/30804760 http://dx.doi.org/10.3389/fncir.2019.00005 |
work_keys_str_mv | AT katzwilliamt dviddistributedversionedimageorienteddataservice AT plazastephenm dviddistributedversionedimageorienteddataservice |