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@ARTICLE{Halchenko:893985,
      author       = {Halchenko, Yaroslav and Meyer, Kyle and Poldrack, Benjamin
                      and Solanky, Debanjum and Wagner, Adina and Gors, Jason and
                      MacFarlane, Dave and Pustina, Dorian and Sochat, Vanessa and
                      Ghosh, Satrajit and Mönch, Christian and Markiewicz,
                      Christopher and Waite, Laura and Shlyakhter, Ilya and de la
                      Vega, Alejandro and Hayashi, Soichi and Häusler, Christian
                      and Poline, Jean-Baptiste and Kadelka, Tobias and Skytén,
                      Kusti and Jarecka, Dorota and Kennedy, David and Strauss,
                      Ted and Cieslak, Matt and Vavra, Peter and Ioanas,
                      Horea-Ioan and Schneider, Robin and Pflüger, Mika and
                      Haxby, James and Eickhoff, Simon and Hanke, Michael},
      title        = {{D}ata{L}ad: distributed system for joint management of
                      code, data, and their relationship},
      journal      = {The journal of open source software},
      volume       = {6},
      number       = {63},
      issn         = {2475-9066},
      reportid     = {FZJ-2021-02965},
      pages        = {3262 -},
      year         = {2021},
      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.},
      cin          = {INM-7},
      ddc          = {004},
      cid          = {I:(DE-Juel1)INM-7-20090406},
      pnm          = {5254 - Neuroscientific Data Analytics and AI (POF4-525)},
      pid          = {G:(DE-HGF)POF4-5254},
      typ          = {PUB:(DE-HGF)16},
      doi          = {10.21105/joss.03262},
      url          = {https://juser.fz-juelich.de/record/893985},
}