When the big-wigs put their heads together to work on pandemic solutions, they need solid datasets full of up-to-date, organized, clean data. But coming up with these datasets is a monumental endeavor. According to IBM: IBM’s new COVID resource is an open-source Jupyter notebook containing pandemic-related datasets and tools derived from authoritative data sources such as John Hopkins University, The New York Times, and the European Centre for Disease Prevention and Control. Policy makers face similar challenges. The United States has over 3,000 counties, each with a unique story of how COVID-19 is impacting its community. As pandemic data changes on a daily basis, the COVID notebook uses Elyra Notebook Pipelines Visual Editor and KubeFlow Pipelines to ensure researchers have clean, up-to-date datasets. In other words, IBM’s taken as many pain-points out of the data aggregation and implementation process as possible. This frees developers and researchers up to focus on the tasks of deep analysis and prediction modeling and gives policy-makers quick, easy access to granular geographic details. For more information check out IBM’s blog post here. You can access COVID notebooks here on GitHub.
