Merge pull request #43 from cct-datascience/colloquium-guidelines

Colloquium guidelines

colloquium.qmd

@@ -0,0 +1,39 @@
+---
+title: "Reproducibility Colloquium"
+---
+
+The [final session](index.qmd#schedule) of this workshop series is our ✨**Reproducibility Colloquium**✨, where you all get a chance to share what you've learned with each other and anyone you'd like to invite to attend.
+You are invited to give a short (about 5min) talk with slides (about 5).
+To make this as low stakes as possible, here is a template you may follow when putting together your presentation.
+
+::: callout-important
+For each slide, you don't need to address **all** of the bullet points—focus on what is relevant for the specific aspects of your project you focused on!
+:::
+
+::: callout-note
+Feel free to adapt this outline—add or remove slides as fits your project.
+:::
+
+-   Slide 1: Super short description of your project for a ***general audience.***[^1]
+-   Slide 2: Describe the data and code components of your project.
+    -   What data types/sources do you work with?
+        -   Hand-collected field data? A data compilation? Instrument data?
+        -   Data type (e.g., numeric, survey responses, DNA sequences, geospatial)?
+        -   File types and sizes?
+    -   What computational tools are you using, and what are you using them for?
+        -   e.g. Excel for data entry; R for data cleaning and analysis; Illustrator for polishing figures
+-   Slide 3: Which aspects of the project did you focus on improving? What was the state of the project before the "makeover"?
+    -   e.g. "I focused on transitioning to using git for version control; previously, I was saving my scripts with a new name each time I worked on them."
+    -   Screen shots of the "before" are encouraged as visuals
+-   Slide 4: What changes did you make as part of the "makeover"?
+    -   Why did you focus on these?
+    -   How did you implement the changes?
+    -   Screen shots of the "after" are encouraged as visuals
+-   Slide 5: Reflections
+    -   What are you most proud of about this?
+    -   Did you run into any challenges?
+    -   What do you see as the next steps?
+
+[^1]: This is a good opportunity to practice an elevator pitch!
+    Try to keep it to just a couple sentences—just enough background to give some context to your data and code.
+    The goal of the presentation is to focus on your project organization and reproducibility, *not* the details of your research topic.

index.qmd

@@ -12,8 +12,7 @@ Welcome to the syllabus for the CCT Data Science fall workshop series: **Reprodu
 
 We'll meet on Tuesdays and Thursdays from 11am to 1pm via Zoom (link pinned in Slack channel)
 
-
-<!-- Edit by editing schedule.csv. To add links, use markdown [text](url) separated by commas. This code turns that into a bulleted list.-->
+<!-- Edit by editing schedule.csv. To add links, use markdown [text](url) separated by commas. This code turns that into a bulleted list. -->
 
 ```{r}
 #| echo: false

schedule.csv

@@ -10,4 +10,4 @@ Lesson,Date,Theme,Topic,Links,Notes
 9,2024-10-01,Repeat & Reproduce,Intermediate R programming II,,iteration (and anonymous functions)
 10,2024-10-03,Document & Publish,Getting credit for your hard work,,"renv, LICENSE, CITATION.cff, Zenodo, GitHub releases"
 11,2024-10-08,Review,Drop-in co-working,,
-12,2024-10-10,Reproducibility Colloquium,An opportunity for you to show off what you've learned,,
+12,2024-10-10,Reproducibility Colloquium,An opportunity for you to show off what you've learned,[guidelines](colloquium.html),