Use Case Examples

In the introductory video of this activity, you were given some ideas on how data science can be used to overcome climate change challenges. In this article, some real-life examples are presented.

Example 1

The World Bank has developed a Climate Change Knowledge Portal (CCKP) as a sort of “one stop shop” for climate-related information, data, and tools. CCKP provides global data on historical and future climate, vulnerabilities, and impacts. It offers climate science research findings to support the decision-making process regarding policies and particular measures to overcome climate change impacts. It also aims to turn knowledge into decision-making with the help of several flexible tools and frameworks. Many researchers and organizations have used this dataset to address climate change related challenges. Examples include using this tool to improve cotton production in Cameroon and identifying impacts of climate change on the water sector in Mexico.

Here is the link to this dataset and tool: https://climateknowledgeportal.worldbank.org/

Example 2

Harvard University also created a dataset called “Harvard Dataverse” for sharing, citing, analyzing, and preserving research data. It is available with open access for everyone worldwide. As an example, this data repository has been used to determine the impact of climate change on coffee production quality in Nicaragua.

To learn more about this, see here: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi%3A10.7910%2FDVN%2FTSUPE1&ref=hackernoon.com

Example 3

In the context of Horizon 2020, a European project called UNaLab mainly focused on developing nature-based solutions (NBS) to fight climate change, and several tools have been developed using big data as well as data visualization techniques. In this project, the IoT Data Collector has been used as the back-end component, that captures data transmitted by a middleware called the IoT Harmonization Middleware, to publish such raw data in the UNaLab database. This data is then usable with another tool called Visual Data Mashup Creator. These combinations of tools create a federated environment where all data (e.g. sensor data, performance results, data extracted from European cities’ IoT platforms, mashed-up data ready for visualization using the NBS Impact Simulator & Monitor, and SDST data) are published as Open Data.

The climate change issues in this project are focused on flooding and storm water management in Tampere, Finland; urban heat stress, air pollution, and lower quality of life in Eindhoven, Netherlands; and intense rainfall on a highly urbanized landscape in Genova, Italy. The tools that collect data from these three cities using various IoT sensors, then visualize the data and the platform will be replicated in some other European cities (e.g., Stavanger, Cannes, Prague, etc.)

For further reading, see here: https://unalab.eu/en

Example 4

The Alan Turing Institute is another example of employing data science related solutions to fight climate change. In one of their projects, they created a new solar forecasting system using available data from sensors which improved day-ahead forecasts for the national grid in the UK by 33%. This approach has enabled them to improve the balance of supply and demand to support greener energy sources like wind and solar.

For further readings, see here: https://www.turing.ac.uk/research/climate-action-turing