The abundance of wildlife occurrence datasets that are currently accessible can be valuable for efforts such as species distribution modeling and range delineation. However, the task of downloading and filtering occurrence records is often complex due to errors and uncertainties that are present in datasets. This repository provides a high-level framework for acquiring and filtering occurrence data that are freely available through the Global Biodiversity Information Facility ([GBIF](https://gbif.org)) API and eBird Basic Dataset ([EBD](https://ebird.org/science/use-ebird-data/)). wildlife-wranger was designed with wildlife occurrence data in mind, and it accounts for numerous issues and challenges related to the application of occurrence records to species distribution modeling. Features that support transparency and build confidence for analyses and evaluations of species distributions are described in the User's Guide.
The abundance of wildlife occurrence datasets that are currently accessible can be valuable for efforts such as species distribution modeling and range delineation. However, the task of downloading and filtering occurrence records is often complex due to errors and uncertainties that are present in datasets. This repository provides a high-level framework for acquiring and filtering occurrence data that are freely available through the Global Biodiversity Information Facility ([GBIF](https://gbif.org)) API and eBird Basic Dataset ([EBD](https://ebird.org/science/use-ebird-data/)). wildlife-wranger was designed with wildlife occurrence data in mind, and it accounts for numerous issues and challenges related to the application of occurrence records to species distribution modeling. Features that support transparency and build confidence for analyses and evaluations of species distributions are described in the User's Guide and a [published abstract] (https://biss.pensoft.net/article/93823/).
In the wildlife-wrangler framework, records are requested from occurrence datasets and filtered according to species- and query-specific parameters. Filtered occurrence records are saved in a database. Options are available to store the details of taxa concepts and filter parameters as JSON files for reuse and reference. Additionally, Jupyter Notebook documents are created that describe the filtered data sets for the sake of documentation and filter set refinement.
In the wildlife-wrangler framework, records are requested from occurrence datasets and filtered according to species- and query-specific parameters. Filtered occurrence records are saved in a database. Options are available to store the details of taxa concepts and filter parameters as JSON files for reuse and reference. Additionally, Jupyter Notebook documents are created that describe the filtered data sets for the sake of documentation and filter set refinement.
