  Computational workflow management systems power contemporary data-intensive
sciences. The slowly resolving reproducibility crisis presents both a sobering
warning and an opportunity to iterate on what science and data processing
entails. The Square Kilometre Array (SKA), the world's largest radio telescope,
is among the most extensive scientific projects underway and presents grand
scientific collaboration and data-processing challenges. This work presents a
scale and system-agnostic computational workflow model and extends five
well-known reproducibility tenets into seven defined for our workflow model.
Subsequent implementation of these definitions, powered by blockchain
primitives, into the Data Activated Flow Graph Engine (DALiuGE), a workflow
management system for the SKA, demonstrates the possibility of facilitating
automatic formal verification of scientific quality in amortized constant time.
We validate our approach with a simple yet representative astronomical
processing task; filtering a noisy signal with a lowpass filter with both CPU
and GPU methods. Our framework illuminates otherwise obscure scientific
discrepancies and similarities between principally identical workflow
executions.
