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Science in big data projects like the ASKAP, MWA and the SKA is enabled by very complex computing workflows turning the original measured quantities into ‘science ready’ data and further on into publications and data releases of final data products. Currently it is very hard if not impossible to re-construct exactly what happened to the original quantities on their long path from measurement to insight. Even for the scientists involved, it is usually virtually impossible to reproduce the exact same result or even describe all the individual steps accurately. If blockchain technology would be used consistently across the complete workflow it could enable such traceability and, in a more advanced implementation, even reproducibility. It could enable re-running the exact same workflow, using the exact same version of processing components and input parameters and cross-checking that the intermediate and final results are the same. Such reproducibility is pretty standard for proper software development projects to ensure that new changes introduced in the software still produce the expected reference results. This project aims to apply good software development practices in combination with blockchain technologies to the process of scientific data analysis in a non-intrusive and transparent way. Since this is not about preventing fraud or tempering, the security aspect of the blockchain technology can be relaxed, which will enable the usage of just locally or not at all distributed ledgers and thus dramatically decrease transaction times.

The student will research this scenario in detail and evaluate the various existing blockchain technologies for suitability. The system will be implemented in an existing workflow system such as DALiuGE. This project will be supervised by Prof. Wicenec.

Example workflow as used in radio astronomy.

We are interested to hear from potential candidates from a computer science or software engineering background with a firm interest in applying this expertise to scientific exploration and knowledge extraction. People with a background in other sciences, but with a solid knowledge of software development practices and tools would be equally suited. The candidate would join an active multi-disciplinary group with many scientific and commercial cross fertilisation possibilities as well as excellent international collaborations.