Code and data supporting the paper "Incremental Material Flow Analysis with Bayesian Inference"
This dataset includes data from the paper "Incremental Material Flow Analysis with Bayesian Inference", derived from real global steel flow data from Cullen et al. (2012). It also includes the code to reproduce the figures, written in Python in the form of Jupyter notebooks. A conda environment file is included to easily set up the necessary Python packages to run the notebooks.
Cite this dataset as:
Lupton, R.,
2017.
Code and data supporting the paper "Incremental Material Flow Analysis with Bayesian Inference".
Zenodo.
Available from: https://doi.org/10.5281/zenodo.581183.
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Creators
Rick Lupton
University of Bath
Contributors
University of Bath
Rights Holder
Documentation
Technical details and requirements:
Format: Python Jupyter notebook (http://jupyter.org), sankeyview (https://github.com/ricklupton/sankeyview). Instructions for setting up a Conda environment with the required software are included in the zip file.
Funders
Engineering and Physical Sciences Research Council
https://doi.org/10.13039/501100000266
Material demand reduction
EP/N02351X/1
Engineering and Physical Sciences Research Council
https://doi.org/10.13039/501100000266
Whole Systems Energy Modelling Consortium (WholeSEM)
EP/K039326/1
Publication details
Publication date: 18 May 2017
by: Zenodo
Version: 1
DOI: https://doi.org/10.5281/zenodo.581183
URL for this record: https://researchdata.bath.ac.uk/id/eprint/802
Related papers and books
Lupton, R. C., and Allwood, J. M., 2017. Incremental Material Flow Analysis with Bayesian Inference. Journal of Industrial Ecology, 22(6), 1352-1364. Available from: https://doi.org/10.1111/jiec.12698.
Contact information
Please contact the Research Data Service in the first instance for all matters concerning this item.
Faculty of Engineering & Design
Mechanical Engineering
