 The UN Sustainable Development Goals, SDGs, require an integrated scientific approach that combines expertise, data, models, and tools across many disciplines. However, this approach poses significant data and computational challenges due to the complexity of the problem. To address these challenges, the US has invested heavily in cyber infrastructure, CI, including data, software, computing resources, and human-centered advancements. Despite these investments, there remain barriers to the adoption of CI in sustainability research, including access to support structures, recruitment and retention of an agile workforce and lack of local infrastructure. To overcome these barriers, we must develop new approaches to data collection, modeling, and decision-making that integrate CI components such as data, software, computing resources, and human-centered advancements. Additionally, we must identify and address the challenges associated with multiscale integration of data and domain-specific models, data availability and usability, uncertainty quantification, mismatch between spatiotemporal scales at which decisions are made and the information generated from scientific analysis and scientific reproducibility. This article was authored by Carol X Song, Pankatishma Wade, Shaan Wang, and others. We are article.tv, links in the description below.