GBIF checklist datasets and data gaps - GBIF Data Blog

A checklist dataset is a bit of a catch-all term describing any dataset that contains primarily a list of taxanomic names. The lines between a checklist dataset and an occurrence dataset can be blurry.


This is a companion discussion topic for the original entry at https://data-blog.gbif.org/post/gbif-checklist-datasets-and-data-gaps/

Since some organizations and countries are already using GBIF occurrences as de facto checklists, maybe national checklists are the land line telephone of biodiversity data and eventually the occurrences in the GBIF network will become the national checklist for a region.

I agree, I think that a lot of countries are skipping the “checklist” step and go straight to collect occurrences instead.

This clearly shows that using checklist to identify data gaps is limited. This could be a good idea for some regions but not everywhere. The problem is that in most cases, when we are missing occurrences, we are also missing checklists. This is never ending. In these cases, the approach that you mentioned in your other post (Hunger mapping) would make more sense.

On the other hand, we have also datasets of Checklist that have Occurrence as extensions, to have the support evidence for each species on the list (e.g Mamíferos de Colombia). It’s necessary to have better guidelines about how we are building and publish Checklist through GBIF.

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I agree. There are many such examples where things could be either a checklist or an occurrence dataset. There has been some discussion that labels need to be more flexible and a dataset could have multiple labels.