Hauptseite > Publikationsdatenbank > Alpaca: a tool to track the provenance of electrophysiology data analysis results > print

001     907334
005     20240313094955.0
037 _ _ |a FZJ-2022-01971
100 1 _ |a Köhler, Cristiano
|0 P:(DE-Juel1)180365
|b 0
|e Corresponding author
111 2 _ |a Meeting of the INCF workgroup (Animal) Neuroscience data structure
|w online
245 _ _ |a Alpaca: a tool to track the provenance of electrophysiology data analysis results
|f 2022-04-20 -
260 _ _ |c 2022
336 7 _ |a Conference Paper
|0 33
|2 EndNote
336 7 _ |a Other
|2 DataCite
336 7 _ |a INPROCEEDINGS
|2 BibTeX
336 7 _ |a LECTURE_SPEECH
|2 ORCID
336 7 _ |a Talk (non-conference)
|b talk
|m talk
|0 PUB:(DE-HGF)31
|s 1654773153_23928
|2 PUB:(DE-HGF)
|x Other
336 7 _ |a Other
|2 DINI
520 _ _ |a Talk presenting the toolbox Alpaca for capturing provenance during the analysis of electrophysiology data, and discussing the potential integration to support provenance in the emerging BIDS-animal-ephys standard that is object of the workgroup.
536 _ _ |a 5235 - Digitization of Neuroscience and User-Community Building (POF4-523)
|0 G:(DE-HGF)POF4-5235
|c POF4-523
|f POF IV
|x 0
536 _ _ |a 5231 - Neuroscientific Foundations (POF4-523)
|0 G:(DE-HGF)POF4-5231
|c POF4-523
|f POF IV
|x 1
536 _ _ |a HDS LEE - Helmholtz School for Data Science in Life, Earth and Energy (HDS LEE) (HDS-LEE-20190612)
|0 G:(DE-Juel1)HDS-LEE-20190612
|c HDS-LEE-20190612
|x 2
536 _ _ |a HBP SGA2 - Human Brain Project Specific Grant Agreement 2 (785907)
|0 G:(EU-Grant)785907
|c 785907
|f H2020-SGA-FETFLAG-HBP-2017
|x 3
536 _ _ |a HBP SGA3 - Human Brain Project Specific Grant Agreement 3 (945539)
|0 G:(EU-Grant)945539
|c 945539
|f H2020-SGA-FETFLAG-HBP-2019
|x 4
536 _ _ |a HAF - Helmholtz Analytics Framework (ZT-I-0003)
|0 G:(DE-HGF)ZT-I-0003
|c ZT-I-0003
|x 5
909 C O |o oai:juser.fz-juelich.de:907334
|p openaire
|p VDB
|p ec_fundedresources
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 0
|6 P:(DE-Juel1)180365
913 1 _ |a DE-HGF
|b Key Technologies
|l Natural, Artificial and Cognitive Information Processing
|1 G:(DE-HGF)POF4-520
|0 G:(DE-HGF)POF4-523
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-500
|4 G:(DE-HGF)POF
|v Neuromorphic Computing and Network Dynamics
|9 G:(DE-HGF)POF4-5235
|x 0
913 1 _ |a DE-HGF
|b Key Technologies
|l Natural, Artificial and Cognitive Information Processing
|1 G:(DE-HGF)POF4-520
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|v Neuromorphic Computing and Network Dynamics
|9 G:(DE-HGF)POF4-5231
|x 1
914 1 _ |y 2022
920 _ _ |l no
920 1 _ |0 I:(DE-Juel1)INM-6-20090406
|k INM-6
|l Computational and Systems Neuroscience
|x 0
920 1 _ |0 I:(DE-Juel1)INM-10-20170113
|k INM-10
|l Jara-Institut Brain structure-function relationships
|x 1
920 1 _ |0 I:(DE-Juel1)IAS-6-20130828
|k IAS-6
|l Theoretical Neuroscience
|x 2
980 _ _ |a talk
980 _ _ |a VDB
980 _ _ |a I:(DE-Juel1)INM-6-20090406
980 _ _ |a I:(DE-Juel1)INM-10-20170113
980 _ _ |a I:(DE-Juel1)IAS-6-20130828
980 _ _ |a UNRESTRICTED
981 _ _ |a I:(DE-Juel1)IAS-6-20130828

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