A new proposal for taxonomic species description is presented to replace
the traditional descriptive texts. This is an attempt to enhance the
species description rate and to make the description output available to
other scientific disciplines, machine learning, lucid identification
keys, big data analysis and its applications. The method consists in
presenting the description of the overall morphology in a coded matrix,
following a character list with detailed observed conditions for each
character. The method is supposed to be dynamic and open to amendments
and new data addition as they become available. We test the new method
describing five new species of Collembola Symphypleona of the genus
Pararrhopalites as a generalized model and made the coded output
available. We conclude that a coded taxonomic description is an advance
to the traditional taxonomic text, with potential to enhance the global
descriptions rate. The generated data is a dynamic matrix that can be
expanded with any data that becomes available, also it can be easily
used in other fields of science, allowing non-experts to access the data
for phylogenetic, biogeographic, ecological studies and big data
analysis. Furthermore, it is a step forward to a general template to
semi-automated taxon recognition and auxiliary tools for species
description using machine learning.