Common things to look out for when post-processing GBIF downloads - GBIF Data Blog

data-blog
1

Here I present a checklist for filtering GBIF downloads.

In this guide, I will assume you are familar with R. This guide is also somewhat general, so your solution might differ. This guide is intended to give you a checklist of common things to look out for when post-processing GBIF downloads.

This is a companion discussion topic for the original entry at https://data-blog.gbif.org/post/gbif-filtering-guide/
3

Dude, cite the DOI, please :slight_smile:

2 Likes
4

Excellent contribution!
I have a question, how to filter those occurrences “saved by default” in which there are no coordinates and because of this the location is located in a central position.

Thanks a lot!

5

If you want to remove country centroids I suggest using CoordinateCleaner::cen(). This might not get all of the centroids, since centroids can be calculated in different ways, but its the easiest solution right now.

1 Like
6

There was a mistake in a previous version of this post that had

filter(coordinateprecision > 0.01 | is.na(coordinateprecision)) %>%

which I changed to …

filter(coordinateprecision < 0.01 | is.na(coordinateprecision)) %>%
7

Hi! Thank you for this post! It appears the package CoordinateCleaner has been removed from CRAN? CRAN - Package CoordinateCleaner
Although previous versions are available in the archive… does this removal mean that the package is unreliable in some way?
Many thanks!
Note: I’ve edited my comment to remove a silly question about alternaitve packages to CoordinateCleaner, you provide a nice list at the end of your post.

8

I assume the package developer knows about the removal and is working on it.

You can still download it and use it with using…

devtools::install_github("ropensci/CoordinateCleaner")
library(CoordinateCleaner)

I would not worry too much about the removal. I am sure it will be back on CRAN soon.

1 Like
9

Good point, thank you!