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Package for managing codelists & attributes for IAMC-format datasets

Project description

nomenclature - Working with IAMC-format project definitions

Copyright 2021-2022 IIASA

This repository is licensed under the Apache License, Version 2.0 (the "License"); see the LICENSE for details.

license DOI python Code style: black pytest ReadTheDocs

Overview

The nomenclature package facilitates validation and processing of scenario data. It allows to manage definitions of data structures for model comparison projects and scenario analysis studies using the data format developed by the Integrated Assessment Modeling Consortium (IAMC).

A data structure definition consists of one or several "codelists". A codelist is a list of allowed values (or "codes") for dimensions of IAMC-format data, typically regions and variables. Each code can have additional attributes: for example, a "variable" has to have an expected unit and usually has a description. Read the SDMX Guidelines for more information on the concept of codelists.

The nomenclature package supports three main use cases:

  • Management of codelists and mappings for model comparison projects
  • Validation of scenario data against the codelists of a specific project
  • Region-processing (aggregation and renaming) from "native regions" of a model to "common regions" (i.e., regions that are used for scenario comparison in a project).

The documentation is hosted on Read the Docs.

Integration with the pyam package

pyam logo

The nomenclature package is designed to complement the Python package pyam, an open-source community toolbox for analysis & visualization of scenario data. The pyam package was developed to facilitate working with timeseries scenario data conforming to the format developed by the IAMC. It is used in ongoing assessments by the IPCC and in many model comparison projects at the global and national level, including several Horizon 2020 & Horizon Europe projects.

The validation and processing features of the nomenclature package work with scenario data as a pyam.IamDataFrame object.

Read the pyam Docs for more information!

Getting started

To install the latest release of the package, please use the following command:

pip install nomenclature-iamc

Alternatively, it can also be installed directly from source:

pip install -e git+https://github.com/IAMconsortium/nomenclature#egg=nomenclature

See the User Guide for the main use cases of this package.

Acknowledgement

openENTRANCE logo

This package is based on the work initially done in the Horizon 2020 openENTRANCE project, 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 for more information.

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

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