A perspective on neuroscience data standardization with Neurodata Without Borders

Neuroscience research has evolved to generate increasingly large and complex experimental data sets, and advanced data science tools are taking on central roles in neuroscience research. Neurodata Without Borders (NWB), a standard language for neurophysiology data, has recently emerged as a powerful...

Full description

Saved in:
Bibliographic Details
Published in:ArXiv.org 2024-01
Main Authors: Pierré, Andrea, Pham, Tuan, Pearl, Jonah, Datta, Sandeep Robert, Ritt, Jason T, Fleischmann, Alexander
Format: Article
Language:English
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites
container_end_page
container_issue
container_start_page
container_title ArXiv.org
container_volume
creator Pierré, Andrea
Pham, Tuan
Pearl, Jonah
Datta, Sandeep Robert
Ritt, Jason T
Fleischmann, Alexander
description Neuroscience research has evolved to generate increasingly large and complex experimental data sets, and advanced data science tools are taking on central roles in neuroscience research. Neurodata Without Borders (NWB), a standard language for neurophysiology data, has recently emerged as a powerful solution for data management, analysis, and sharing. We here discuss our labs' efforts to implement NWB data science pipelines. We describe general principles and specific use cases that illustrate successes, challenges, and non-trivial decisions in software engineering. We hope that our experience can provide guidance for the neuroscience community and help bridge the gap between experimental neuroscience and data science.
format article
fullrecord <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_10593085</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2881246824</sourcerecordid><originalsourceid>FETCH-LOGICAL-p1125-6bed60370c058d7ff8c1593b14c426b240dc14607a879ac34836f80bab1aa8d83</originalsourceid><addsrcrecordid>eNpVkF1LwzAUhoMobsz9BemlN4V8tcmuZA51wlAExctwmqQu0jU1SSf66606ZV6dc3hfngfOARpTxkguOaWHe_sITWN8wRjTUtCiYMdoxIQUDBM6RvfzrLMhdlYnt7WZb7PW9sFH7WyrbWYgQRYTtAaCcR-Q3NB4c2md3X7VvuOn4fR9yi58MAPqBB3V0EQ73c0Jery6fFgs89Xd9c1ivso7QmiRl5U1JWYCa1xII-paalLMWEW45rSsKMdGE15iAVLMQDMuWVlLXEFFAKSRbILOf7hdX22s0bZNARrVBbeB8K48OPU_ad1aPfutInjwYFkMhLMdIfjX3sakNi5q2zTQWt9HRaUklJeS8qF6ui_7s_w-kn0CdUtyVQ</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2881246824</pqid></control><display><type>article</type><title>A perspective on neuroscience data standardization with Neurodata Without Borders</title><source>Publicly Available Content Database</source><creator>Pierré, Andrea ; Pham, Tuan ; Pearl, Jonah ; Datta, Sandeep Robert ; Ritt, Jason T ; Fleischmann, Alexander</creator><creatorcontrib>Pierré, Andrea ; Pham, Tuan ; Pearl, Jonah ; Datta, Sandeep Robert ; Ritt, Jason T ; Fleischmann, Alexander</creatorcontrib><description>Neuroscience research has evolved to generate increasingly large and complex experimental data sets, and advanced data science tools are taking on central roles in neuroscience research. Neurodata Without Borders (NWB), a standard language for neurophysiology data, has recently emerged as a powerful solution for data management, analysis, and sharing. We here discuss our labs' efforts to implement NWB data science pipelines. We describe general principles and specific use cases that illustrate successes, challenges, and non-trivial decisions in software engineering. We hope that our experience can provide guidance for the neuroscience community and help bridge the gap between experimental neuroscience and data science.</description><identifier>ISSN: 2331-8422</identifier><identifier>EISSN: 2331-8422</identifier><identifier>PMID: 37873012</identifier><language>eng</language><publisher>United States: Cornell University</publisher><ispartof>ArXiv.org, 2024-01</ispartof><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,37012</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37873012$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Pierré, Andrea</creatorcontrib><creatorcontrib>Pham, Tuan</creatorcontrib><creatorcontrib>Pearl, Jonah</creatorcontrib><creatorcontrib>Datta, Sandeep Robert</creatorcontrib><creatorcontrib>Ritt, Jason T</creatorcontrib><creatorcontrib>Fleischmann, Alexander</creatorcontrib><title>A perspective on neuroscience data standardization with Neurodata Without Borders</title><title>ArXiv.org</title><addtitle>ArXiv</addtitle><description>Neuroscience research has evolved to generate increasingly large and complex experimental data sets, and advanced data science tools are taking on central roles in neuroscience research. Neurodata Without Borders (NWB), a standard language for neurophysiology data, has recently emerged as a powerful solution for data management, analysis, and sharing. We here discuss our labs' efforts to implement NWB data science pipelines. We describe general principles and specific use cases that illustrate successes, challenges, and non-trivial decisions in software engineering. We hope that our experience can provide guidance for the neuroscience community and help bridge the gap between experimental neuroscience and data science.</description><issn>2331-8422</issn><issn>2331-8422</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNpVkF1LwzAUhoMobsz9BemlN4V8tcmuZA51wlAExctwmqQu0jU1SSf66606ZV6dc3hfngfOARpTxkguOaWHe_sITWN8wRjTUtCiYMdoxIQUDBM6RvfzrLMhdlYnt7WZb7PW9sFH7WyrbWYgQRYTtAaCcR-Q3NB4c2md3X7VvuOn4fR9yi58MAPqBB3V0EQ73c0Jery6fFgs89Xd9c1ivso7QmiRl5U1JWYCa1xII-paalLMWEW45rSsKMdGE15iAVLMQDMuWVlLXEFFAKSRbILOf7hdX22s0bZNARrVBbeB8K48OPU_ad1aPfutInjwYFkMhLMdIfjX3sakNi5q2zTQWt9HRaUklJeS8qF6ui_7s_w-kn0CdUtyVQ</recordid><startdate>20240122</startdate><enddate>20240122</enddate><creator>Pierré, Andrea</creator><creator>Pham, Tuan</creator><creator>Pearl, Jonah</creator><creator>Datta, Sandeep Robert</creator><creator>Ritt, Jason T</creator><creator>Fleischmann, Alexander</creator><general>Cornell University</general><scope>NPM</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20240122</creationdate><title>A perspective on neuroscience data standardization with Neurodata Without Borders</title><author>Pierré, Andrea ; Pham, Tuan ; Pearl, Jonah ; Datta, Sandeep Robert ; Ritt, Jason T ; Fleischmann, Alexander</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p1125-6bed60370c058d7ff8c1593b14c426b240dc14607a879ac34836f80bab1aa8d83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><toplevel>online_resources</toplevel><creatorcontrib>Pierré, Andrea</creatorcontrib><creatorcontrib>Pham, Tuan</creatorcontrib><creatorcontrib>Pearl, Jonah</creatorcontrib><creatorcontrib>Datta, Sandeep Robert</creatorcontrib><creatorcontrib>Ritt, Jason T</creatorcontrib><creatorcontrib>Fleischmann, Alexander</creatorcontrib><collection>PubMed</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>ArXiv.org</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pierré, Andrea</au><au>Pham, Tuan</au><au>Pearl, Jonah</au><au>Datta, Sandeep Robert</au><au>Ritt, Jason T</au><au>Fleischmann, Alexander</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A perspective on neuroscience data standardization with Neurodata Without Borders</atitle><jtitle>ArXiv.org</jtitle><addtitle>ArXiv</addtitle><date>2024-01-22</date><risdate>2024</risdate><issn>2331-8422</issn><eissn>2331-8422</eissn><abstract>Neuroscience research has evolved to generate increasingly large and complex experimental data sets, and advanced data science tools are taking on central roles in neuroscience research. Neurodata Without Borders (NWB), a standard language for neurophysiology data, has recently emerged as a powerful solution for data management, analysis, and sharing. We here discuss our labs' efforts to implement NWB data science pipelines. We describe general principles and specific use cases that illustrate successes, challenges, and non-trivial decisions in software engineering. We hope that our experience can provide guidance for the neuroscience community and help bridge the gap between experimental neuroscience and data science.</abstract><cop>United States</cop><pub>Cornell University</pub><pmid>37873012</pmid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2331-8422
ispartof ArXiv.org, 2024-01
issn 2331-8422
2331-8422
language eng
recordid cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_10593085
source Publicly Available Content Database
title A perspective on neuroscience data standardization with Neurodata Without Borders
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-10T12%3A14%3A38IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20perspective%20on%20neuroscience%20data%20standardization%20with%20Neurodata%20Without%20Borders&rft.jtitle=ArXiv.org&rft.au=Pierr%C3%A9,%20Andrea&rft.date=2024-01-22&rft.issn=2331-8422&rft.eissn=2331-8422&rft_id=info:doi/&rft_dat=%3Cproquest_pubme%3E2881246824%3C/proquest_pubme%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-p1125-6bed60370c058d7ff8c1593b14c426b240dc14607a879ac34836f80bab1aa8d83%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2881246824&rft_id=info:pmid/37873012&rfr_iscdi=true