Data Science Core

PROJECT SUMMARY - DATA SCIENCE CORE Significance: Effective climate change actions are hampered by a lack of transdisciplinary and community- informed data, fragmented health surveillance systems, and insufficient local and regional climate data. Community engagement is pivotal for meaningful data collection and effective policy change, yet challenges

arise from the digital divide. An integrative data approach, and advanced data science methods, such as 'climate computing', can address these complexities and lead to effective and sustainable climate–health policies and ensure their adoption with community involvement. Innovation: Central to our Data Science Core (DSC) is a

groundbreaking initiative: the union of data science with deep, reciprocal community interaction. Our team aims to embed community feedback into every facet of research, including data collection, synthesis, and dissemination of results. Historically, community-focused research and bioinformatics have been distinct fields.

This initiative strives to bridge the gap by “bringing the power of data to all the stakeholders.” Our proposed approach includes: 1) a revolutionary, crowdsourced, community-based data collection system, in which data is relevant and actionable, 2) a holistic approach to data integration, combining diverse disciplines, 3) advanced

data analysis using Artificial Intelligence (AI) and Machine Learning (ML), and 4) effective communication of results to all stakeholders, including community, academia, government, and public. Our team has extensive experience in developing and applying analytical techniques and public interfaces that can enrich research

projects facilitated by the Center. Building upon prior work of community-engaged data science from national to local scales, the proposed research activities will consist of three primary aims: 1) Community Integration with Data which underscores the importance of embedding community feedback into our data foundations. The DSC

will develop state-of-the-art informatics tools to effectively engage communities, including, an AI-assisted tool translating findings into digestible insights for the wider public, 2) Real-World Data Commons which revolves around the creation of a prototype integrating community insights with multifaceted data on climate, policy, and

health. It will also serve as a public resource, providing scripts, datasets, and visualization tools that ensures community voices are central, through collaboration with the Community Engagement Core, and 3) Analytical Support which provides robust analytics for the center's various projects. This includes advanced air quality

monitoring and modeling, with integration of ML to enhance forecasting accuracy. Overall impact: The DSC’s proposed infrastructure is poised to set a precedent whereby it serves as a national blueprint for climate policy researchers. Adhering NIH data sharing principles, this infrastructure will act as a comprehensive repository for

diverse data on climate policy and health. The ultimate vision of DSC is to harness cutting-edge and equity- centered data science tools and insights to guide the development of policies aimed at countering the adverse effects of climate change on public health, benefiting not just the state of Wisconsin, but the nation and globe.