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Credibility building activities in computational research include verification and validation, reproducibility and replication, and uncertainty quantification. Though orthogonal to each other, they are related. This paper presents validation and replication studies in electromagnetic excitations on nanoscale structures, where the quantity of interest is the wavelength at which resonance peaks occur. The study uses the open-source software PyGBe : a boundary element solver with treecode acceleration and GPU capability. We replicate a result by Rockstuhl et al. (2005, doi:10/dsxw9d) with a two-dimensional boundary element method on silicon carbide (SiC) particles, despite differences in our method. The second replication case from Ellis et al. (2016, doi:10/f83zcb) looks at aspect ratio effects on high-order modes of localized surface phonon-polariton nanostructures. The results partially replicate: the wavenumber position of some modes match, but for other modes they differ. With virtually no information about the original simulations, explaining the discrepancies is not possible. A comparison with experiments that measured polarized reflectance of SiC nano pillars provides a validation case. The wavenumber of the dominant mode and two more do match, but differences remain in other minor modes. Results in this paper were produced with strict reproducibility practices, and we share reproducibility packages for all, including input files, execution scripts, secondary data, post-processing code and plotting scripts, and the figures (deposited in Zenodo). In view of the many challenges faced, we propose that reproducible practices make replication and validation more feasible. This article is part of the theme issue ‘Reliability and reproducibility in computational science: implementing verification, validation and uncertainty quantification in silico ’.
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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.
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- Award ID(s):
- 1637320
- PAR ID:
- 10128989
- Date Published:
- Journal Name:
- Proceedings IEEE Conference on Big Data
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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