The four-step biomes workflow | 1. Occurrence records | 2. The 31 biome schemes | Next

Goal | 1. Rank the schemes for your data | Rank within one biome definition | 2. Inspect the ranking | Next

Goal | 1. Classify occurrence records into biomes | 2. Common variations | Next

Goal | 1. Tabulate records per biome | 2. Visualise the workflow | The whole workflow in one call | Done

Installing sampbias | Input data | 1. Species occurrence records | 2. Geographic gazetteers | Running an analysis | Output | Changing default settings | Custom study area | Equal area grid

Background | Identifying erroneous coordinates with CoordinateCleaner | Install CoordinateCleaner | Set up libraries and data | Visualize the data on a map | Use CoordinateCleaner to automatically flag problematic records | Option A) Using the clean_coordinates wrapper function | Option B) Using the magrittr pipe (%>%) | Temporal outliers | Improving data quality using GBIF meta-data | Improving data quality using external information | Flag records based on fixed longitude and latitude | Flag records based on species natural ranges | Identifying problematic data sets | Identify dataset with ddmm to dd.dd conversion error | Test for rasterized sampling | References

Background | Install CoordinateCleaner | Load required libraries | Load test dataset | Visualize the records on a map | CoordinateCleaner | Spatial issues | Temporal issues | Improving data quality using meta-data | Basic taxonomy | Spatial coordinates | Time | Conclusions