These three workshops are designed to provide participants with an introduction into the application and potential of geometric morphometric (GMM) methodologies for archaeological science. The first workshop introduces participants to the theoretical underpinnings of statistical shape and form analysis, from landmark options, data creation, data transformation, data analysis and visualisation. The second workshop will be an R-based introduction to two- and three-dimensional landmark-based GMM, while the third workshop focuses on two-dimensional outline analyses (Elliptic Fourier Analysis). 'Tidy' approaches to GMM data transformation and visualisation will be emphasised throughout the workshop. While the workshop is limited to 50 participants, all code, presentations and material (including videos) will be accessible.
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Session 1 (13th July / 14:00-16:00): Introduction to GMM (via Zoom/Slack)
Presentation: https://cshoggard.github.io/-gmm_liverpool_2020/workshop_one/presentation.html#1
Video: https://github.com/CSHoggard/-gmm_liverpool_2020/releases/tag/v1 -
Session 2 (20th July / 14:00-16:00): Landmark-based GMM in R (via Zoom/Slack)
Video: https://github.com/CSHoggard/-gmm_liverpool_2020/releases/tag/v2 -
Session 3 (27th July / 14:00-16:00): Outline-based GMM in R (via Zoom/Slack)
Video: https://github.com/CSHoggard/-gmm_liverpool_2020/releases/tag/v3
All data input, manipulation and analyses will be performed in the R Environment. Data will be imported directly throughout the R Markdown (see relevant folders). Please ensure R/RStudio and all files are downloaded onto your computer or laptop before or at the beginning of the second workshop. Software including IDAV Landmark Editor and the TPS-series of packages will also be showcased.
All participants will be invited to a Slack workspace. This workspace will provide an interface between the instructor, organisers and participants, and facilitate further dialogue.
For more information please contact lucyjt@liverpool.ac.uk.
We thank the Arts and Humanities Research Council North West Consortium Doctoral Training Partnership (AHRC NWCDTP) for supporting this workshop.
Adams, D.C. and Otárola-Castillo, E. (2013). Geomorph: an r package for the collection and analysis of geometric morphometric shape data. Methods of Ecology and Evolution 4, 393-399.
Adams, D.C., Rohlf, F.J. and Slice, D.E. (2004). Geometric morphometrics: ten years of progress following the ‘revolution’. Italian Journal of Zoology, 71, 5–16.
Bonhomme, V., Picq, S., Gaucherel, C., and Claude, J. (2014). Momocs: Outline analysis using R. Journal of Statistical Software, 56, 1–24.
Bookstein, F.L. (1991). Morphometric Tools for Landmark Data: Geometry and Biology. New York: Cambridge University Press.
Kovarovic, K., Aiello, L. C., Cardini, A. and Lockwood, C. A. (2011). Discriminant function analyses in archaeology: Are classification rates too good to be true? Journal of Archaeological Science, 38(11), 3006–3018.
MacLeod, N. (1999). Generalizing and extending the Eigenshape method of shape space visualization and analysis. Paleobiology, 25 (1), 107–138.
Slice, D.E. (2007). Geometric Morphometrics, Annual Review of Anthropology 36(1), 261–281.
Yoshioka, Y. (2004). Analysis of petal shape variation of Primula sieboldii by elliptic fourier descriptors and principal component analysis. Annals of Botany, 94(5), 657–664.
Zelditch, M.L., Swiderski D.L., Sheets H.D. and Fink, W.L. (2004). Geometric morphometrics for biologists: a primer. San Diego (CA): Elsevier Academic Press.