8 ppl attended
Organisational matters
- The twitter team asks for input. Please see the etherpad document here: https://etherpad.wikimedia.org/p/ssla-tweets
- Reminder that we have a Google calendar and everyody is invited to add relevant events in and around computational archaeology: https://calendar.google.com/calendar/embed?src=uitkaq4o6b90gbcca2bh1qqa3g%40group.calendar.google.com
Conferences, meetings and sessions
- CAA2022: To our knowledge the conference date is still unknown
- Georg Roth forwarded an invitation to a math lecture related to geometric morphometrics: https://www.math-berlin.de/academics/bms-fridays. The relevant working group has a website here: https://morphomatics.github.io
As part of the current Thematic Einstein Semester on “Mathematics of Imaging in Real-Word Challenges“,
a series of tandem tutorials will be held throughout the winter semester 2021/22.
These tutorials will take place as online lectures from 2 to 4 pm (Berlin time) on:
- Friday, 29 October 2021: "Classical vs. Data Driven Regularization Methods in Imaging"
- **Friday, 26 November 2021: "Population wide Medical Image and Shape Analysis"**
- Friday, 18 February 2022: "Neural MRI"
SIG activities
- Teaching material list: Sophie Schmidt has shared a google document in the respective slack channel. Please invest some minutes of brainstorming to add the relevant materials you know.
Show and tell
- James Allison presented R code to parse, transform and analyse the output of the Agent-based “Village model” software: https://github.com/jallison7/village-output-analysis
- Some relevant feedback items:
- Plotly might simplify interactive data analysis (https://plotly.com/r/,
ggplotly()
) - Stream processing might be useful to summarise large text files that do not fit into memory (e.g. https://gist.github.com/nevrome/2d13733583d9f0c0dfaadc4c0b12aedf)
- “Split-Apply-Combine” workflows can be implemented nicely with dplyr’s
group_by
+summarize
(e.g. https://datacarpentry.org/R-genomics/04-dplyr.html#split-apply-combine_data_analysis_and_the_summarize()_function) - High performance computing environments for model runs can also be rented, if no such infrastructure is available (e.g. https://towardsdatascience.com/how-to-run-rstudio-on-aws-in-under-3-minutes-for-free-65f8d0b6ccda)
- Plotly might simplify interactive data analysis (https://plotly.com/r/,
- Some relevant feedback items: