How can we trust the integrity of results from research that relies on computations without repeating them? By certifying the successful original execution of a computational workflow that produced findings in situ. With certifications in hand, consumers of research can trust the transparency of results without necessarily repeating computations. Learn more...
The TRACE project is developing techniques and tools for certifying the results of computational research. This includes the creation of technical specifications for describing and certifying research artifacts as well as the development of reusable software tools>. Learn more...
Research communities across the sciences are requiring that authors share the data, code, and methods used to obtain computational results. However, without verification by repeating computations, there is no guarantee that provided artifacts are complete or can actually be used to produce reported results. Learn more...
Particularly problematic are studies that employ sensitive or proprietary data for which access and reuse are restricted; streaming, transient, or ephemeral data that cannot be used to verify reproducibility due to their dynamic nature; or very large-scale or specialized computational resources available only to authorized users. In these cases, verification by repeating computations may not be possible.
The TRACE project is addressing challenges in trusting and verifying the results of computational research. The integrity of results is uncertain when their lineage or production cannot be validated, but verification through repeating executions is expensive and inefficient -- when possible. TRACE is developing a model of certified transparency whereby the original execution of a computational workflow is certified by the system on which they were run.