Week 1

Agenda Day 1. Synthesis & Unix Day 2. Communication and Version Control Day 3. Advanced Unix and Data tools Day 4. Open Data and R Day 5. People and Data Wrangling
8:15-8:30 Welcome (Jones, Budden) Feedback, questions, and discussion Feedback, questions, and discussion Feedback, questions, and discussion Feedback, questions, and discussion
8:30-9:00 Participant intros; brief bio, project interests, goals for course (all) Activity: Version control, Git, Github, Git in RStudio (Brun) Advanced unix tools (awk, sed, iconv, etc.) (Jones) Ecological Metadata in R (Mecum) Social aspects of collaboration, high-performing groups, data policies (Budden and Jones)
9:00-9:30 Course overview, discussion of expectations (Jones, Budden) Activity: Version control, Git, Github, Git in RStudio (Brun) Advanced unix tools (awk, sed, iconv, etc.) (Jones) Open data in R and ROpenSci (Mecum & Jones) Facilitating group discussions (Budden)
9:30-9:45 Break Break Break Break Break
9:45-11:00 Intro to servers, networks, and the unix command line (Jones) Activity: Version control, Git, Github, Git in RStudio (Brun) Bash shell scripts (Jones) Data liberation (scraping, text mining) (Brun) Introduction to tidyverse wrangling (Lortie)
11:00-12:00 Thinking preferences activity (Budden) Activity: Version control, Git, Github, Git in RStudio (Brun) R Review/ Assessment (Mecum) Data liberation (scraping, text mining) (Brun) Tutorial and exercises wrangling to filter, sort, and merge (Lortie)
Noon-1:00 Lunch Lunch Lunch Lunch Lunch
1:00-1:30 R Markdown & Rstudio setup (Mecum) Communications: The message box (Budden) Data Management & Scientific data repositories (Budden) Regular expressions (Mecum) Data munging, QA/QC, cleaning (Mecum)
1:30-2:00 R Markdown & Rstudio setup (Mecum) Group work on message box (Budden) Publishing Data in R (Jones) Message box 2: Group exchange and feedback (Budden) Data munging, QA/QC, cleaning (Mecum)
2:00-2:15 Break Break Break Break Break
2:15-5:00 Pre-Assessment (Budden) and Synthesis Groups (Jones) Synthesis Groups Synthesis Groups Synthesis Groups Synthesis Groups
5:00-5:15 Peanut Gallery Peanut Gallery Peanut Gallery Peanut Gallery Peanut Gallery


Week 2

Agenda Day 6. Open Meta-analysis Day 7. Tabular Data Day 8. Programming and Workflows Day 9. Reproducible research Day 10. Metagenomics
8:15-8:30 Feedback, questions, and discussion Feedback, questions, and discussion Mid-term assessment Feedback, questions, and discussion Feedback, questions, and discussion
8:30-9:00 Metas and systematic reviews (Lortie) Overview of tabular data modeling (Jones) Lecture: Workflows and software modeling (Jones) LECTURE: Science in the open: Provenance and Reproducibility (Jones) Introduction to metagenomic data (Teal)
9:00-9:30 Metas steps 1-3 (Lortie) Data Modeling Exercise with Group projects (Jones) Wrangling followup: tidyr’s separate, gather, and spread Activity: Asserting provenance in R (Jones) Metagenomics (Teal)
9:30-9:45 Break Break Break Break Break
9:45-11:00 Metas step 4 (Lortie) Activity: SQL and PostgreSQL (Jones) Activity: Functions and modular code in R (Jones) Practical provenance (Lowndes) Metagenomics (Teal)
11:00-12:00 Metas step 5 (Lortie) Activity: SQL and PostgreSQL (Jones) Activity: Creating R Packages (Jones) Activity: Recording provenance with recordr (Jones) Metagenomics (Teal)
Noon-1:00 Lunch (starts 11:45) Lunch Lunch Lunch Lunch
1:00-1:30 LAB: complete group metas (Lortie) SQL and database access in R (Mecum) Testing R code and analysis (Mecum) Activity: Reproducible papers with Rmd (Mecum and Jones) Advanced Metagenomics (Teal)
1:30-2:00 Presentations by groups of meta-analyses SQL and database access in R (Mecum) Workflow design activity (Group projects) (Jones) Activity: Reproducible papers with Rmd Hands-on exercise and workflow (Teal)
2:00-2:15 Break Break Break Break Break
2:15-5:00 Synthesis Groups Synthesis Groups Synthesis Groups Synthesis Groups Synthesis Groups
5:00-5:15 Peanut Gallery Peanut Gallery Peanut Gallery Peanut Gallery Peanut Gallery


Week 3

Agenda Day 11. Geospatial Data Day 12. Geospatial analysis and Algorithmic Approaches Day 13. Data Viz Day 14. Scaling up analysis Day 15. Group projects! Publications. Group reports
8:15-8:30 Feedback, questions, and discussion Feedback, questions, and discussion Feedback, questions, and discussion Feedback, questions, and discussion Feedback, questions, and discussion
8:30-9:00 Intro to GIS - geospatial data concepts (Wasser) LAB: geospatial analysis (Wasser) Data Viz and interactive tools (Mecum) Parallel processing (in R)(Jones) Group 1 presentation and discussion
9:00-9:30 Go from an Excel-like set of data to QGIS (Brun) LAB: geospatial analysis (Wasser) Data Viz and interactive tools (Mecum) Parallel processing (in R)(Jones) Group 1 presentation and discussion
9:30-9:45 Break Break Break Break Break
9:45-11:00 Intro to GIS in R (Wasser & Mecum) LAB: geospatial analysis (Wasser) Data Viz and interactive tools (Mecum) Open Science (Lortie) (10-10:30)
Synthesis Groups
Group 2 presentation and discussion
11:00-12:00 Intro to GIS in R (Wasser & Mecum) LAB: geospatial analysis (Wasser) Perfunctory Python (Brun) (30 mins) Synthesis Groups Group 3 presentation and discussion
Noon-1:00 Lunch Lunch Lunch Lunch Lunch
1:00-1:30 Publishing maps to the web in R (Mecum) LAB: NetCDF and HDF5 (Wasser & Mecum) Synthesis Groups Synthesis Groups Post-course assessment
1:30-2:00 Publication ready maps in R (Mecum) LAB: NetCDF and HDF5 (Wasser & Mecum) Synthesis Groups Synthesis Groups Discussion: open science for synthesis and course feedback
2:00-2:15 Break Break Break Break Break
2:15-5:00 Synthesis Groups Synthesis Groups Synthesis Groups Synthesis Groups Adjourn
5:00-5:15 Peanut Gallery Peanut Gallery Peanut Gallery Peanut Gallery Celebration