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Collective Knowledge: Towards R&D sustainability

Research funding bodies strongly encourage research projects to disseminate discovered knowledge and transfer developed technology to industry. Unfortunately, capturing, sharing, reproducing and building upon experimental results has become close to impossible in computer systems' R&D. The...

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Bibliographic Details
Main Authors: Fursin, Grigori, Lokhmotov, Anton, Plowman, Ed
Format: Conference Proceeding
Language:English
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Summary:Research funding bodies strongly encourage research projects to disseminate discovered knowledge and transfer developed technology to industry. Unfortunately, capturing, sharing, reproducing and building upon experimental results has become close to impossible in computer systems' R&D. The main challenges include the ever changing hardware and software technologies, lack of standard experimental methodology and lack of robust knowledge exchange mechanisms apart from publications where reproducibility is still rarely considered. Supported by the EU FP7 TETRACOM Coordination Action, we have developed Collective Knowledge (CK), an open-source framework and methodology that involves the R&D community to solve the above problems collaboratively. CK helps researchers gradually convert their code and data into reusable components and share them via repositories such as GitHub, design and evolve over time experimental scenarios, replay experiments under the same or similar conditions, apply state-of-the-art statistical techniques, crowdsource experiments across different platforms, and enable interactive publications. Importantly, CK encourages the continuity and sustainability of R&D efforts: researchers and engineers can build upon the work of others and make their own work available for others to build upon. We believe that R&D sustainability will lead to better research and faster commercialization, thus increasing return-on-investment.
ISSN:1558-1101