DISCUSSION
To access the global species diversity, it is mandatory to enhance the description rates of new taxa, mainly where the diversity is least known. A description protocol that can communicate the morphologic characters in a coded notation, allows the application of new technologies in the research and machine learning, which may be a major turnover in the discipline, and affect the species description rates. The scarcity of trained taxonomists and the hermeticity of the taxonomic description manuscripts, are the biggest barriers to the advance of the knowledge on the species diversity and evolutionary processes of diversification, both clue elements to understand the global diversity decline.
In the study of Collembola, as well as in many other groups, the information content of a traditional taxonomic text is often difficult to access and cannot be transported to analytical software without a detailed revision of the species description, which many times demands an expert in the taxon. The traditional format is also almost impossible to be used for machine learning, as there are many differences in the presentation of the data, that can make the comparison among different manuscripts impossible to non-experts and to artificial intelligence. The open character list of the coded description allows easy insertion and correction of the information, and either the character lists, the chaetae banks and the coded species descriptions are fully compatible with technologies that work with data matrices.
Our results can be synthesized in the following conclusions:
1 – The coded taxonomic description is a notation method that produces interchangeable data, fully available for different scientific disciplines. The data can be used by non-specialists for different purposes in science.
2 – The method makes it possible to add any source of new data to the description when it became available. It is dynamic and open as a continuous list of characters, the updating of the knowledge of a given species is not dependent of a traditional taxonomic revision.
3 – The method allows machine learning that can help to speed the species description rates and taxon identification where they are least known. This can be an important tool to fight global diversity crisis.
4 – Coded description is meant to Collembola but may be applied to any taxonomic group, reducing the ambiguity of narrative descriptions. When it is widely used, the comparative analysis will be almost a straightforward process.