Synthetic populations of South African urban areas

Published: 27 Apr 2018 | Version 1 | DOI: 10.17632/dh4gcm7ckb.1
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Description of this data

The data accompanying this article include the compressed, Extensible Markup Language (XML) files of the synthetic populations for the nine areas of importance in South Africa. The provided populations are controlled at the household level using (household) income, and at individual levels using gender and population group. The result provides a complete stock of individuals while accounting for detailed demographic, socioeconomic information, and household structure.

The detailed XML Schema Definition (XSD) and XML Document Type Definition (DTD), which contains the declarations that describes the formal acceptable structure of the XML file, is available on http://www.matsim.org/files/dtd/. More specifically, there is one XSD definition for the household file, households_v1.0.xsd, and one DTD file for the individuals, population_v6.dtd. The files are normal XML and readable using many parsers. Our choice to use the Multi-Agent Transport Simulation (MATSim) infrastructure is because the populations are, in our context, frequently used for large-scale mesoscopic transport models using the agent-based MATSim.

Experiment data files

Steps to reproduce

The detailed description of the steps to reproduce is published in the Data-in-Brief article (link to follow) with the same title as this data set.

This data is associated with the following publication:

Synthetic populations of South African urban areas

Published in: Data in Brief

Latest version

  • Version 1

    2018-04-27

    Published: 2018-04-27

    DOI: 10.17632/dh4gcm7ckb.1

    Cite this dataset

    Joubert, Johan W. (2018), “Synthetic populations of South African urban areas”, Mendeley Data, v1 http://dx.doi.org/10.17632/dh4gcm7ckb.1

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Categories

Population, Extensible Markup Language, Synthesis, Agent-Based Modeling, South Africa, Household

Licence

CC BY 4.0 Learn more

The files associated with this dataset are licensed under a Creative Commons Attribution 4.0 International licence.

What does this mean?

This dataset is licensed under a Creative Commons Attribution 4.0 International licence. What does this mean? You can share, copy and modify this dataset so long as you give appropriate credit, provide a link to the CC BY license, and indicate if changes were made, but you may not do so in a way that suggests the rights holder has endorsed you or your use of the dataset. Note that further permission may be required for any content within the dataset that is identified as belonging to a third party.

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