Scientific Visualization and Reproducibility for "Open" Environmental Science

Practicing reproducible scientific research requires access to appropriate reproducibility methodology and software, as well as open data. Strict reproducibility in complex scientific domains such as environmental science, ecology and medicine, however, is difficult if not impossible. Here, we consider replication as a relaxed but bona fide substitution for strict reproducibility and propose using 3D terrain visualization for replication in environmental science studies that propose causal relationships between one or more driver variables and one or more response variables across complex ecosystem landscapes. We base our contention of the usefulness of visualization for replication on more than ten years observing environmental science modelers who use our 3D terrain visualization software to develop, calibrate, validate, and integrate predictive models. To establish the link between replication and model validation and corroboration, we consider replication as proposed by Munafò, i.e., triangulation. We enumerate features of visualization systems that would enable such triangulation and argue that such systems would render feasible domain-specific, open visualization software for use in replicating environmental science studies.