The Legacy of Spatial Apartheid Machine Learning Challenge Data (ICPSR 38810)

Name: The Legacy of Spatial Apartheid Machine Learning Challenge Data
Published: 2023-06-15
License: https://www.icpsr.umich.edu/web/ICPSR/studies/38810/terms

Version Date: Jun 15, 2023 View help for published

Principal Investigator(s): View help for Principal Investigator(s)
Raesetje Sefala, Distributed Artificial Intelligence Research Institute (DAIR); Timnit Gebru, Distributed Artificial Intelligence Research Institute (DAIR); Nyalleng Moorosi, Google; Richard Klein, University of the Witwatersrand

https://doi.org/10.3886/ICPSR38810.v1

Version V1 (see more versions)

V2 [2023-06-16] unpublished
V1 [2023-06-16] unpublished

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Summary View help for Summary

The dataset was created from data classifying neighbourhoods in South Africa According to 4 neighbourhood types: Wealthy (a combination of the classes Suburb, Smallholdings, Farm), Non-wealthy (combination of Township, Informal area, Collective living Quarters, Village), Non-Residential (combination of Industrial area, Commercial land, Parks and Recreational Areas, Vacant) and Background.

These data are to be used for a machine learning challenge put on by Zindi.

The specific application the authors created the larger dataset for is to enable researchers and policymakers to quantify the effects of spatial apartheid over time, for the specific purpose of helping to uncover and working to reverse its effects. Those data will be available at a later date.

Citation View help for Citation

Sefala, Raesetje, Gebru, Timnit, Moorosi, Nyalleng, and Klein, Richard. The Legacy of Spatial Apartheid Machine Learning Challenge Data. [distributor], 2023-06-15. https://doi.org/10.3886/ICPSR38810.v1

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Funding View help for Funding

South Africa. Department of Science and Technology, Council for Scientific and Industrial Research (CSIR), Google, Deep Learning Indaba and Nvidia

Subject Terms View help for Subject Terms

Apartheid image recognition machine learning satellite images societal impact

Geographic Coverage View help for Geographic Coverage

South Africa

Restrictions View help for Restrictions

These data are specifically for those entering the Zindi competition associated with the data. Please use Application for DAIR Zindi data to apply for access.

Once your application is submitted, we will review the application. If approved, you will then be granted access to the data.

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Data Collection Notes View help for Data Collection Notes

There are no data files to be downloaded. The only way to access these data is through applying.
Inquiries about the larger dataset should be submitted to icpsr-help@umich.edu referencing RCMD and the DAIR data.

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