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.

Keywords:
Sankey diagram, flow data, visualisation, Material Flow Analysis, steel

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.

Departments:

Faculty of Engineering & Design
Mechanical Engineering