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https://github.com/openENTRANCE/openentrance
Definitions of common terms (variables, regions, etc.) for the openENTRANCE project
https://github.com/openENTRANCE/openentrance
Last synced: 3 months ago
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Definitions of common terms (variables, regions, etc.) for the openENTRANCE project
- Host: GitHub
- URL: https://github.com/openENTRANCE/openentrance
- Owner: openENTRANCE
- License: apache-2.0
- Created: 2020-03-13T14:21:37.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2024-06-06T10:32:30.000Z (5 months ago)
- Last Synced: 2024-06-11T17:42:01.302Z (5 months ago)
- Language: Python
- Homepage: http://openentrance.eu
- Size: 944 KB
- Stars: 30
- Watchers: 16
- Forks: 49
- Open Issues: 39
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- open-sustainable-technology - openENTRANCE - The Horizon 2020 openENTRANCE project aims at developing, using and disseminating an open, transparent and integrated modeling platform for assessing low-carbon transition pathways in Europe. (Energy Systems / Regional Energy System Models)
README
# Project definitions for the openENTRANCE project
Copyright 2020-2023 openENTRANCE consortium
This repository is licensed under the Apache License, Version 2.0 (the "License"); see
the [LICENSE](LICENSE) for details.
[](https://github.com/openENTRANCE/openentrance/blob/main/LICENSE)
[](https://github.com/openENTRANCE/openentrance)
[](https://github.com/psf/black)
## Aim and scope of this repository
The [Horizon 2020 openENTRANCE project](https://openentrance.eu) aims at
developing, using and disseminating an open, transparent and integrated
modelling platform for assessing low-carbon transition pathways in Europe.
A key requirement for an effective linking of models and consistent analysis is
a common "nomenclature", i.e., shared lists of variables, regions and units
used across the entire project.
This repository makes available the nomenclature used within the consortium and
serves as a discussion platform for extending the lists of terms.
*We invite other modelling teams to contribute and join the discussion,
hoping to facilitate increased cooperation across research projects
on (European) energy and climate policy!*
## How to work with this repository
There are several ways to interact with the nomenclature and definitions
provided in this repository. The simplest approach is to just read the `yaml`
files on GitHub - see the links [below](#Timeseries-data-dimensions).
The repository is structured so that it can be parsed by the
Python package **nomenclature** for scenario ensemble validation and processing.
Read more on [GitHub](https://github.com/iamconsortium/nomenclature)!
### An installable Python package
To facilitate using the definitions in data processing workflows and scripts,
there is an installable Python package with several utility
functions and dictionaries. [More information](openentrance)
## Data format structure
The openENTRANCE project uses a **common data format** based on a template
developed by the [Integrated Assessment Modeling Consortium (IAMC)](https://www.iamconsortium.org/)
and already in use in many model comparison projects at the global and national
level. While the IAMC comprises (mostly) integrated-assessment teams, the data
format is generic and can be used for a wide range of applications, including
energy-systems analysis or modelling of specific sectors like transport,
industry or the building stock.
### Timeseries data dimensions
In the data format, every timeseries is described by six dimensions (codes):
1. Model - [more information](definitions/model)
2. Scenario - [more information](definitions/scenario)
3. Region - [more information](definitions/region)
4. Variable - [more information](definitions/variable)
5. Unit - see the section on [variables](definitions/variable)
for details
6. Subannual (optional, default 'Year')[1] -
[more information](definitions/subannual)
In addition to these six dimensions, every timeseries is described by
a set of **year-value** pairs.
The resulting table can be either shown as
- **wide format** (see example below, with *years* as columns), or
- **long format** (two columns *year* and *value*).
| **model** | **scenario** | **region** | **variable** | **unit** | **subannual** | **2015** | **2020** | **2025** |
|-------------|---------------------|------------|----------------|----------|---------------|---------:|---------:|---------:|
| GENeSYS-MOD | Societal Commitment | Europe | Primary Energy | EJ/y | Year | 69.9 | 65.7 | ... |
| ... | ... | ... | ... | ... | ... | ... | ... | ... |
Data via the [IAMC 1.5°C scenario explorer](https://data.ene.iiasa.ac.at/iamc-1.5c-explorer),
showing a scenario from the [CD-LINKS](https://www.cd-links.org) project.
[1] *The index 'Subannual' is an extension of the original format introduced by
the openENTRANCE project to accomodate data at a subannual temporal resolution.*
### Recommended usage of this data format
The Python package **pyam** was developed to facilitate working with timeseries
data conforming to this structure. Features include validation of values,
aggregation and downscaling of data, and import/export with various file formats
(`xlsx`, `csv`, ...) and table layouts (wide vs. long data).
[Read the docs](https://pyam-iamc.readthedocs.io) for more information!
## Funding acknowledgement
This project has received funding from the European Union’s Horizon 2020 research
and innovation programme under grant agreement No. 835896.