“In production and development, open source as a development model promotes universal access via an open-source or free license to a product’s design or blueprint, and universal redistribution of that design or blueprint, including subsequent improvements to it by anyone”.
In the computing domain, “Open Source Software (OSS) is computer software with its source code made available with a license in which the copyright holder provides the rights to study, change, and distribute the software to anyone and for any purpose.”
A scientific article based on data analysis through sophisticated software tools and applications is not the scholarship itself, it is merely an advertising of the scholarship. The actual scholarship is the complete software development environment, along with the complete data, and the complete set of instructions which generated the figures .
Furthermore, D. C. Ince et al.  state that “scientific communication relies on evidence that cannot be entirely included in publications, but the rise of computational science has added a new layer of inaccessibility. Although it is now accepted that data should be made available on request, the current regulations regarding the availability of software are inconsistent. […] The vagaries of hardware, software and natural language will always ensure that exact reproducibility remains uncertain, but withholding code increases the chances that efforts to reproduce results will fail”.
For all the above, real science reproducibility should include full access to papers and to the whole set of data and computer tools, and Open Science is the only viable approach to turn this vision into a reality.
The Sci-GaIA project consortium is very much committed to Open Source and all the code developed for/used by the project is available on GitHub at:
- The Sci-GaIA Project
- Africa & Arabia Regional Operation Centre
- Catania Science Gateway Framework
- Open Science Catania
and it is released under the Apache 2.0 licence.
 Jonathan B. Buckheit and David L. Donoho, “WaveLab and Reproducible Research”, Lecture Notes in Statistics Volume 103, 1995, pp 55-81, http://goo.gl/JvGSGB.
 Darrel C. Ince, Leslie Hatton and John Graham-Cumming, “The case for open computer programs”, Nature 482, p. 485–488 (23 February 2012), doi:10.1038/nature10836.