tue_overview.Rmd

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title: "Day 2 - Overview"
output: html_document
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# Learning objectives
After this day you will be able to:

1. Judge the quality of geo-referenced species occurrences obtained from public databases for downstream analyses in biogeography and conservation

2. Improve the reliability of datasets of geo-referenced occurrences using automated algorithms and software in R

3. Quantify the effect of geographic sampling bias in a datasets of geo-referenced occurrences

4. Generate summary visualizations of species richness including species richness maps.

# Detailed schedule

### Lectures (live)
13:15 - 15:00
- Lecture "Challenges to spatial big data in biogeography and tools to address them"
- Demonstration + hands on in break out rooms 

15:00 - 17:00
- Lecture "Bracatus: a method for probabilistic quality assessment of biogeographic records
- Demonstration

### Exercises (asynchronous)

1. Cleaning geographic and fossil records (optional) from public databases
2. Quantifying sampling bias in datasets of occurrence records
3. Probabilistic cleaning with Bracatus
4. Species ranges and richness


# Exercise outcome
A the end of this day, you will have produced the following files for your group of interest, which you will use during the exercises during the next days:

1. A .csv file with cleaned occurrence records based on threshold filtering

2. A .csv file with probabilistic estimates of records correctness and biogeographic status 

3. Two figures quantifying the effect of sampling bias in your dataset of occurrence records

4. A figure with the distribution of species richness in your group of interest