Data Sources and Tutorials Now Available!

Data Sources and Tutorials Now Available!

The official data sources for the 2019-20 Modeling the Future Challenge projects have now been released. With this year’s theme – agriculture, water, and climate change – the amount of data available for students to research is staggering. One of the main challenges for teams will be in narrowing the scope of the project to be manageable. To help facilitate access to data that will be important for each team, we have provided a number of different data sources that may be used. In this year’s challenge, there is one primary data set that must be used in all projects. We also provide several supporting data sets that are available but not required to be used by any team.

Primary Data Set: The USDA’s Risk Management Agency’s Crop Insurance Data: This data provides information about insurance policies and claims from the Federal Crop Insurance Company (FCIC). Data from this source should be used to model historic trends in agricultural losses and project future changes that may be expected due to changes in climate factors or water access.

Supporting Data Sets: several additional resources are highlighted to help teams focusing on specific climate factors or who are looking for specific types of relationships to include in their models. Some teams may find these resources valuable, others may not. It is completely up to the team to determine whether they want to include data from these sources in their projects.

Teams are not limited to these data sets. There are many sites available that have additional data. Particularly, once a team selects the region for their project, they may find additional information and data specific to that region from local government websites. We encourage teams to look beyond the data we provide to supplement their project. The only data requirement is that you use the crop insurance information from the Risk Management Agency to model future risks and potential losses to the crops you are researching.

Find descriptions, links, and tutorials for each of the data sets here.