Publication:
Reproducibility and efficiency in handling complex neurophysiological data

dc.bibliographiccitation.artnumber000010151520200041
dc.bibliographiccitation.issue0
dc.bibliographiccitation.journalNeuroforum
dc.bibliographiccitation.volume0
dc.contributor.authorDenker, Michael
dc.contributor.authorGrün, Sonja
dc.contributor.authorWachtler, Thomas
dc.contributor.authorScherberger, Hansjörg
dc.date.accessioned2023-10-06T22:51:30Z
dc.date.available2023-10-06T22:51:30Z
dc.date.issued2021
dc.description.abstractAbstract Preparing a neurophysiological data set with the aim of sharing and publishing is hard. Many of the available tools and services to provide a smooth workflow for data publication are still in their maturing stages and not well integrated. Also, best practices and concrete examples of how to create a rigorous and complete package of an electrophysiology experiment are still lacking. Given the heterogeneity of the field, such unifying guidelines and processes can only be formulated together as a community effort. One of the goals of the NFDI-Neuro consortium initiative is to build such a community for systems and behavioral neuroscience. NFDI-Neuro aims to address the needs of the community to make data management easier and to tackle these challenges in collaboration with various international initiatives (e.g., INCF, EBRAINS). This will give scientists the opportunity to spend more time analyzing the wealth of electrophysiological data they leverage, rather than dealing with data formats and data integrity.
dc.identifier.doi10.1515/nf-2020-0041
dc.identifier.urihttps://resolver.sub.uni-goettingen.de/purl?gro-2/136958
dc.item.fulltextNo Fulltext
dc.language.isoen
dc.notes.internDOI-Import WOS-2023-10-07
dc.relation.eissn2363-7013
dc.relation.issn0947-0875
dc.titleReproducibility and efficiency in handling complex neurophysiological data
dc.typejournal_article
dc.type.internalPublicationyes
dspace.entity.typePublication

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