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001     1019361
005     20231214201905.0
024 7 _ |a 10.5281/ZENODO.10010615
|2 doi
024 7 _ |a 10.34734/FZJ-2023-05331
|2 datacite_doi
037 _ _ |a FZJ-2023-05331
041 _ _ |a English
100 1 _ |a Szczepanik, Michał
|0 P:(DE-Juel1)190195
|b 0
|e Corresponding author
111 2 _ |a INM Retreat 2023
|c Jülich
|d 2023-10-17 - 2023-10-18
|w Germany
245 _ _ |a Lightweight data publishing on Jülich Data with DataLad
|f 2023-10-17 -
260 _ _ |c 2023
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 1702479697_3807
|2 PUB:(DE-HGF)
|x Other
336 7 _ |a Other
|2 DINI
520 _ _ |a Jülich DATA is the central institutional repository for research data of the Research Center Jülich and supports sharing, preserving, citing, exploring, and analyzing research data with descriptive metadata, without hosting large files. In this tutorial, participants will discover how DataLad can integrate with Dataverse and have the best of both worlds: Discoverability and metadata with Jülich DATA, and actionable data tracking with DataLad. With conceptual and hands-on elements, we will learn how to publish or clone lightweight DataLad datasets to and from Jülich DATA.
536 _ _ |a 5254 - Neuroscientific Data Analytics and AI (POF4-525)
|0 G:(DE-HGF)POF4-5254
|c POF4-525
|f POF IV
|x 0
536 _ _ |a SFB 1451 INF - Datenmanagement für computergestützte Modellierung (INF) (458705875)
|0 G:(GEPRIS)458705875
|c 458705875
|x 1
588 _ _ |a Dataset connected to DataCite
773 _ _ |a 10.5281/ZENODO.10010615
856 4 _ |y OpenAccess
|u https://juser.fz-juelich.de/record/1019361/files/Lightweight_Juelich_Data_Datalad-1.pdf
856 4 _ |y OpenAccess
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856 4 _ |y OpenAccess
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856 4 _ |y OpenAccess
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856 4 _ |y OpenAccess
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909 C O |o oai:juser.fz-juelich.de:1019361
|p openaire
|p open_access
|p VDB
|p driver
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 0
|6 P:(DE-Juel1)190195
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)POF4-525
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-500
|4 G:(DE-HGF)POF
|v Decoding Brain Organization and Dysfunction
|9 G:(DE-HGF)POF4-5254
|x 0
914 1 _ |y 2023
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
920 1 _ |0 I:(DE-Juel1)INM-7-20090406
|k INM-7
|l Gehirn & Verhalten
|x 0
980 _ _ |a talk
980 _ _ |a VDB
980 _ _ |a UNRESTRICTED
980 _ _ |a I:(DE-Juel1)INM-7-20090406
980 1 _ |a FullTexts

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