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@INPROCEEDINGS{Grn:892659,
      author       = {Grün, Sonja and Denker, Michael},
      title        = {{A}pproaches for improving rigor and efficiency in sharing
                      complex neurophysiological data},
      reportid     = {FZJ-2021-02245},
      year         = {2021},
      abstract     = {Sharing complex neurophysiological data, e.g. in a
                      collaboration or in a publication, in such a way that
                      theycan be understood and used is a challenge. Issues to be
                      solved are to define adequate metadatarepresentations to
                      describe the experiment, find standardized formats to store
                      the data, or to capture thedetails of the data preprocessing
                      workflows. For most of these challenges easy or generic
                      solutions do notyet exist that could be used “out of the
                      box”. Where solutions do exist, the knowledge and
                      expertise on howto employ them in the context of a
                      particular experiment is often scattered in the community.
                      Inconsequence, the implementation of a research data
                      management strategy in an experimental laboratory isoften a
                      balance act between ensuring a certain level of rigor,
                      reproducibility and documentation on the onehand, and
                      efficiency (in terms of time and personnel) of designing and
                      implementing strategies on the otherhand.Moreover, the
                      results of this balancing act may turn out to be
                      frustrating: even with comparatively highinvestment in
                      improving the quality of data and metadata descriptions and
                      data curation process, the resultwill often be disappointing
                      in the sense that the benefits associated with good research
                      data managementare not realized. This holds in particular
                      when a lack of standards for data formats, structures, and
                      commonvocabulary prevents the curated dataset to be easily
                      (e.g., automatically) used by other scientists, analyzedby
                      existing tools, or integrated into data stores. Thus,
                      despite the efforts, the data remain difficult to use
                      andcomprehend. Moreover, the solutions for data management
                      developed on a project-by-project basis, whilebased on
                      promising ideas, are rarely developed to a level of
                      stability and generality required forstandardization, and
                      tend to be lost after the project’s lifetime.To overcome
                      this unsatisfactory situation, we here argue for the need to
                      promote the level of standardizationas a community effort.
                      To this end, we analyze the process of data acquisition and
                      preprocessing ofelectrophysiological data [1,2]. This
                      example includes a number of aspects that tend to complicate
                      the datacuration process, such as a data acquisition process
                      that spans over multiple years of a running experiment,or
                      the need for collaboration across labs. We describe the
                      steps that we required to accomplish the goal ofcurating
                      data to a degree that they become sharable and publishable
                      in sufficient detail to ensure easy andunsupervised reuse in
                      data analysis workflows [3]. In this endeavor, we consider
                      conceptual considerationsunderlying the design of the data
                      acquisition and curation process and highlight the
                      standardizationstrategies and tools (e.g., [4-7]) that can
                      help in reducing the effort of handling the data. Some of
                      these toolsare coordinated and harmonized as part of the
                      EBRAINS e-infrastructure for neuroscience [8], which
                      iscommitted to contribute and shape a layer of interoperable
                      compute and data services for futureneuroscience. Likewise
                      we will outline the needs where complementary
                      standardization is still non-adequateor non-existent, and
                      suggest how community efforts coordinated by the NFDI-Neuro
                      consortium [9] couldaddress, seed, and drive towards
                      concrete solutions. Getting into a habit of treating the
                      design of datamanagement for new experiments early on in
                      harmony with community standards and recommendations
                      willgive scientists the opportunity to spend more time
                      analyzing the wealth of electrophysiological data
                      theyleverage with low-barrier collaborations, rather than
                      dealing with data formats and data integrity.},
      month         = {Mar},
      date          = {2021-03-22},
      organization  = {14th Meeting of the German
                       Neuroscience Society, Online (Online),
                       22 Mar 2021 - 30 Mar 2021},
      cin          = {INM-6 / INM-10 / IAS-6},
      cid          = {I:(DE-Juel1)INM-6-20090406 / I:(DE-Juel1)INM-10-20170113 /
                      I:(DE-Juel1)IAS-6-20130828},
      pnm          = {523 - Neuromorphic Computing and Network Dynamics
                      (POF4-523) / 5235 - Digitization of Neuroscience and
                      User-Community Building (POF4-523) / 5231 - Neuroscientific
                      Foundations (POF4-523) / HBP SGA3 - Human Brain Project
                      Specific Grant Agreement 3 (945539) / HMC - Helmholz
                      Metadata Collaboration $((DE-HGF)HMC_20200306)$},
      pid          = {G:(DE-HGF)POF4-523 / G:(DE-HGF)POF4-5235 /
                      G:(DE-HGF)POF4-5231 / G:(EU-Grant)945539 /
                      $G:(DE-HGF)HMC_20200306$},
      typ          = {PUB:(DE-HGF)1},
      url          = {https://juser.fz-juelich.de/record/892659},
}