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Neuroinformatics

, Volume 14, Issue 1, pp 23–40 | Cite as

A Digital Repository and Execution Platform for Interactive Scholarly Publications in Neuroscience

  • Victoria Hodge
  • Mark Jessop
  • Martyn Fletcher
  • Michael Weeks
  • Aaron Turner
  • Tom Jackson
  • Colin Ingram
  • Leslie Smith
  • Jim Austin
Original Article

Abstract

The CARMEN Virtual Laboratory (VL) is a cloud-based platform which allows neuroscientists to store, share, develop, execute, reproduce and publicise their work. This paper describes new functionality in the CARMEN VL: an interactive publications repository. This new facility allows users to link data and software to publications. This enables other users to examine data and software associated with the publication and execute the associated software within the VL using the same data as the authors used in the publication. The cloud-based architecture and SaaS (Software as a Service) framework allows vast data sets to be uploaded and analysed using software services. Thus, this new interactive publications facility allows others to build on research results through reuse. This aligns with recent developments by funding agencies, institutions, and publishers with a move to open access research. Open access provides reproducibility and verification of research resources and results. Publications and their associated data and software will be assured of long-term preservation and curation in the repository. Further, analysing research data and the evaluations described in publications frequently requires a number of execution stages many of which are iterative. The VL provides a scientific workflow environment to combine software services into a processing tree. These workflows can also be associated with publications and executed by users. The VL also provides a secure environment where users can decide the access rights for each resource to ensure copyright and privacy restrictions are met.

Keywords

Interactive publications Collaboration Reproducible neuroscience Interactive publication repository Execution platform Web portal Scientific workflows 

Notes

Acknowledgments

The CARMEN VL was developed under funding provided by the UK Engineering and Physical Sciences Research Council (grant number EP/E002331/1) and development of the VL is now supported by the UK Biotechnology and Biological Sciences Research Council (grant number BB/I000984/1).

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of YorkYorkUK
  2. 2.Institute of NeuroscienceNewcastle UniversityNewcastle upon TyneUK
  3. 3.Department of Computing Science and MathematicsUniversity of StirlingStirlingUK

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