University of Washington
My main research activities combine models from evolutionary ecology with analyses of archaeological evidence to investigate past human behaviour. Specific interests include the hominin disperal into mainland Southeast Asia, forager technologies and ecology in Australia, mainland Southeast Asia and elsewhere. A common theme in all my work is a commitment to the techniques and methods for reproducible research. I use the R programming language, Markdown, and related tools and services to improve the computational reproducibility of my research. I also use these tools in my teaching.
Marwick, B., Boettiger, C., & Mullen, L. (2018). Packaging data analytical work reproducibly using R (and friends). The American Statistician, 72(1), 80-88.
#- We update the concept of the 'research compendium' using R and related tools and services.
Marwick, B., & Birch, S. E. P. (2018). A Standard for the Scholarly Citation of Archaeological Data as an Incentive to Data Sharing. Advances in Archaeological Practice, 6(2), 125-143.
#- We study data availability in archaeology journal articles and data repositories. We explore definitions of data and ethics of data sharing
Marwick, B., d’Alpoim Guedes, J., Barton, C. M., Bates, L. A., Baxter, M., Bevan, A., ... & Conrad, C. (2017). Open science in archaeology. SAA Archaeological Record, 17(4), 8-14.
#- A large-group authored manifesto to motivate open science practices in archaeology, and outline what practices make sense for most archaeologists
Marwick, B. (2017). Computational reproducibility in archaeological research: basic principles and a case study of their implementation. Journal of Archaeological Method and Theory, 24(2), 424-450.
#- A detailed report on a case of study of how to make a typical archaeological report reproducible using R and related tools and services.
Eglen, S. J., Marwick, B., Halchenko, Y. O., Hanke, M., Sufi, S., Gleeson, P., ... & Wachtler, T. (2017). Toward standard practices for sharing computer code and programs in neuroscience. Nature Neuroscience, 20(6), 770.
#- A manifesto including concrete, hands-on steps that researchers can take to make their code available with their research.