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The Role of Data Science and Analytics to Achieve SDGs

This article presents some positive impacts that data science has had on the environmental SDGs.
The fight against climate change issues may benefit from data science in many ways. Data Science, including machine learning and data analytics, enables us to apply modern methods to develop new and alternative decisions based on data sources. By gathering data on sustainability related issues, industries can generate intuitions that drive their sustainability initiatives.

To measure progress towards the sustainable development goals, UN has launched an SDG tracker. This tracker is developed based on the data gathered across all available indicators worldwide. Several data analytics and data visualization techniques have been employed to develop this tool.

The tracker is openly accessible via this website:

There are several examples of using data science to achieve the SDGs. One example is sustainable cities and communities (i.e., SDG 11), where satellite remote sensing enables us to track encroachment on public land or spaces such as parks and forests. As another example, combining satellite imagery, crowd-sourced witness accounts and open data helps us track drought, deforestation, and so forth. This is closely related to SDG 13, namely climate action.

Responsible consumption and production (SDG 12) can also gain from data science by utilizing online search patterns or e-commerce transactions which may uncover the pace of transitioning to energy efficient products and services.

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Data Science for Climate Change

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