Opening the Black Box: Enabling Transparency in Scientific Computation
Reproducibility, enabled by transparency in reporting, is the gold standard for science. It is not systematically repeating scientific research, but the potential to do so that maintains high quality in research practice. Reproducibility also drives scientific advance because it enables new research to build on prior accomplishments. This ethos is especially effective because it emerged from within the scientific community.
Archaeology espouses this reproducibility ethos, made all the more important because archaeological practice can destroy the integrity of its data. But transparency for computational archaeological research has not yet received the consideration afforded to other archaeological practice. This is increasingly important as computational archaeology—spanning mining, synthesis, and visualization of large, complex datasets, to modeling and simulation of social dynamics—become more prevalent.
We describe community initiatives for promoting transparency in computational archaeology. The CoMSES Net Computational Model Library is a framework for publishing computational code, so that it can be used by others and authors can be credited for their work through citations. The MIRACLE project is developing cloud-based environments for reproducible workflows of complex, computational analyses of large, multi-dimensional datasets. These initiative share the goal of encouraging and enabling transparency and reproducibility in scientific computation.
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This Resource is Part of the Following Collections
- Society for American Archaeology 80th Annual Meeting, San Francisco, CA (2015) •
- Open methods in archaeology: how to encourage reproducible research as the default practice
Cite this Record
Opening the Black Box: Enabling Transparency in Scientific Computation. C. Michael Barton, Marco Janssen, Dawn Parker, Allen Lee, Sean Bertin. Presented at The 80th Annual Meeting of the Society for American Archaeology, San Francisco, California. 2015 ( tDAR id: 397312)