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

TitleA Digital Repository and Execution Platform for Interactive Scholarly Publications in Neuroscience
Publication TypeJournal Article
Year of Publication2016
AuthorsHodge, V, Jessop, M, Fletcher, M, Weeks, M, Turner, A, Jackson, T, Ingram, C, Smith, L, Austin, J
Volume14
Issue1
Pagination23 - 40
Date Published2016/01/01
ISBN Number1559-0089
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.

URLhttps://doi.org/10.1007/s12021-015-9276-3
Short TitleNeuroinformatics
D1 Cited or Publication: 
DataONE Cited