Repeatability and Re-usability in Scientific Processes: Process Context, Data Identification and Verification

eScience offers huge potential of speeding up scientific discovery, being able to flexibly re-use, combine and build on top of existing tools and results. Yet, to reap the benefits we must be able to actually perform these activities, i.e. having the data, processing components etc. available for redeployment and being able to trust them. Thus, repeatability of e-Science experiments is a requirement of validating work to establish trust in results. This proves challenging as procedures currently in place are not set up to meet these goals. Several approaches have tackled this issue from various angles. This paper reviews these building blocks and ties them together. It starts from the capture and description of entire research processes and ways to document them. Regarding data, we review the recommendations of the Research Data Alliance on how to precisely identify arbitrary subsets of potentially high-volume and highly dynamic data used in a process. Last, we present mechanisms for verifying the correctness of process reexecutions.

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