![Zoanthus_sansibaricus-iNat-NSathe.jpg](https://static.wixstatic.com/media/28d1b1_2c9bb2485449403393b137698b1959b1~mv2.jpg/v1/fill/w_980,h_553,al_c,q_85,usm_0.66_1.00_0.01,enc_auto/28d1b1_2c9bb2485449403393b137698b1959b1~mv2.jpg)
GBIO framework:
evidence
The Evidence focus area deals with refining, structuring and evaluating the data, to improve quality and place it within a taxonomic framework that organizes all known information about any species.
Provide organized access to biodiversity information regardless of origin
Build infrastructure to index and organize major classes of biodiversity information, to facilitate rapid discovery and reuse and to support development of a comprehensive biodiversity knowledge graph.
Photo: Zoanthus sansibaricus. Photo by Nikhil Sathe via iNaturalist Research-grade Observations, licensed under CC BY-NC 4.0. link.
Fitness-for-use and annotation
Enable the expert community to manage and curate biodiversity data
Develop tools and processes to enable amateurs, experts and automated systems, to correct and annotate data elements that improve quality and fitness-for-use for user requirements, ensuring that all annotations are permanently accessible.
Taxonomic framework
Maintain a stable and comprehensive catalogue of species
Complete and maintain an expert-curated catalogue of all species, including data on names, classification and phylogeny, and incorporating taxa lacking formal names.
Integrated occurrence data
Organize all evidence for the recorded occurrence of species in time and space
Bring together data from all relevant sources to document the occurrence and abundance of all species throughout the world, at the finest possible scales and for all time periods, and support evaluation of the coverage, completeness and quality of these resources.
Aggregated species trait data
Capture all available trait information for any species and interactions between species
Aggregate all available data and information on species traits and interactions in forms suitable for use in digital analysis and modelling.