Although not perfect, there are several open data sources that could be very useful to assess basic indicators related to demography, settlement morphology and human health
What is the project about?
This project part of an interdisciplinary collaboration between researchers from CEAT (EPFL), the Swiss Tropical and Public Health Institute (Swiss TPH) and the University of Basel.
The research advances a framework strictly based on open-access data and open source software to address common questions (and challenges) related to urban planning in the so-called Global South. It was a proof-of-concept study showing how freely accessible materials and software could be used to understand the morphology (and quality) of urban settlements, and how different urban morphologies could be associated to different health outcomes – in this case, diarrheal diseases.
Why Open?
From a practical perspective, as researchers we see the value of openly sharing materials and tools with our peers in order to advance knowledge. For instance, our study could not be done without open-access resources. Moreover, from an ethical point of view, any publicly funded research should be openly accessible and share all used materials (including code), as long as data privacy allows for it.
Who benefits from it?
Our study focused primarily on planning officials who often struggle in finding the right data to support decision-making, notably in low-income settings. Our study showed that, although not perfect, there are several open data sources that could be very useful to assess basic indicators related to demography, settlement morphology and human health. Such indicators are essential to urban (and human) development anywhere and, thanks to recent advances in remote sensing and geospatial technologies, these indicators can now be easily estimated.
How did you make it Open Data?
Our study was published in an open-access journal, and is available here. The datasets, software (notebooks in Python language) and local environment used to run the analysis are all available in our Github page. It has been recently published and has not required maintenance so far.
This study would not have been possible witouth the invaluable contribution of Jérôme Chenal (EPFL), Brama Koné (CSRS), Martí Bosch (EPFL) and Jürg Utzinger (SwissTPH).
Contact: Vitor Pessoa Colombo