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Journal Article

DataLad: distributed system for joint management of code, data, and their relationship

Authors

Halchenko,  Yaroslav O.
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Meyer,  Kyle
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Poldrack,  Benjamin
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Solanky,  Debanjum Singh
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Wagner,  Adina S.
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Gors,  Jason
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MacFarlane,  Dave
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Pustina,  Dorian
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Sochat,  Vanessa
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Ghosh,  Satrajit S.
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Mönch,  Christian
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Markiewicz,  Christopher J.
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Waite,  Laura
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Shlyakhter,  Ilya
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de la Vega,  Alejandro
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Hayashi,  Soichi
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Häusler,  Christian Olaf
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Poline,  Jean-Baptiste
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Kadelka,  Tobias
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Skytén,  Kusti
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Jarecka,  Dorota
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Kennedy,  David
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Strauss,  Ted
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Cieslak,  Matt
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Vavra,  Peter
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Ioanas,  Horea-Ioan
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Schneider,  Robin
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/persons/resource/Mika.Pflueger

Pflüger,  Mika
Potsdam Institute for Climate Impact Research;

Haxby,  James V.
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Eickhoff,  Simon B.
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Hanke,  Michael
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No external resources are shared
Fulltext (public)

25737oa.pdf
(Publisher version), 882KB

Supplementary Material (public)
There is no public supplementary material available
Citation

Halchenko, Y. O., Meyer, K., Poldrack, B., Solanky, D. S., Wagner, A. S., Gors, J., MacFarlane, D., Pustina, D., Sochat, V., Ghosh, S. S., Mönch, C., Markiewicz, C. J., Waite, L., Shlyakhter, I., de la Vega, A., Hayashi, S., Häusler, C. O., Poline, J.-B., Kadelka, T., Skytén, K., Jarecka, D., Kennedy, D., Strauss, T., Cieslak, M., Vavra, P., Ioanas, H.-I., Schneider, R., Pflüger, M., Haxby, J. V., Eickhoff, S. B., Hanke, M. (2021): DataLad: distributed system for joint management of code, data, and their relationship. - Journal of Open Source Software, 6, 63, 3262.
https://doi.org/10.21105/joss.03262


Cite as: https://publications.pik-potsdam.de/pubman/item/item_25737
Abstract
DataLad is a Python-based tool for the joint management of code, data, and their relationship,built on top of a versatile system for data logistics (git-annex) and the most popular distributedversion control system (Git). It adapts principles of open-source software development anddistribution to address the technical challenges of data management, data sharing, and digitalprovenance collection across the life cycle of digital objects. DataLad aims to make datamanagement as easy as managing code. It streamlines procedures to consume, publish, andupdate data, for data of any size or type, and to link them as precisely versioned, lightweightdependencies. DataLad helps to make science more reproducible and FAIR (Wilkinson et al.,2016). It can capture complete and actionable process provenance of data transformations toenable automatic re-computation. The DataLad project (datalad.org) delivers a completelyopen, pioneering platform for flexible decentralized research data management (RDM) (Hanke,Pestilli, et al., 2021). It features a Python and a command-line interface, an extensiblearchitecture, and does not depend on any centralized services but facilitates interoperabilitywith a plurality of existing tools and services. In order to maximize its utility and target audience, DataLad is available for all major operating systems, and can be integrated intoestablished workflows and environments with minimal friction.