nomenclature: Working with IAMC-style scenario data

Release v0.3.dev18+gef7fa98.

license python black pytest rtd


The nomenclature package facilitates working with “codelists” that follow the format developed by the Integrated Assessment Modeling Consortium (IAMC). Codelists are yaml file based lists of allowed values (or codes) for dimensions of IAMC-style data, for example regions and variables. Using these codelists, nomenclature performs data validation to check if a provided data set conforms to the values in the code lists.

Additionally, it can execute “region processing”, which consists of renaming of “native regions” and/or aggregation to “common regions” used in a project.

Those two tasks are carried out by two classes:

  1. The DataStructureDefinition class handles the validation of scenario data. It contains data templates for variables (including units) and regions to be used in a model comparison or scenario exercise following the IAMC data format.

  2. The RegionProcessor class carries out renaming and aggregation based on information given in yaml model mapping files.

Instructions on how to install nomenclature can be found in the “Installation” section.

The complete user guide including the file specifications for codelists and model mappings, example code and details on how to use nomenclature is given in “User Guide”.

Table of Contents



This package is based on the work initially done in the Horizon 2020 project openENTRANCE, which aims to develop, use and disseminate an open, transparent and integrated modelling platform for assessing low-carbon transition pathways in Europe.

Refer to the openENTRANCE/openentrance repository on GitHub for more information.


This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 835896.