Advancing urban research through cutting-edge AI, machine learning, and data visualization technologies. Transforming how cities understand, analyze, and optimize urban environments.
Tackling critical challenges in urban computing through innovative approaches
We will deploy a cloud-based, open collaborative environment that supports the use of OSCUR over large and diverse urban datasets (e.g., spatiotemporal, geometry, image). This will make it easy for users to quickly create analyses that are reproducible by design, and that can be debugged, shared, and extended. Drawing upon our prior experience in building computational reproducibility tools, we will also integrate systematic provenance capture into the tools and libraries available in OSCUR, enabling reproducibility even for analyses carried out outside the cloud environment.
While there are many datasets available, they are distributed over many repositories and come in different formats and granularities. Besides, most repositories provide search interfaces that are limited to keyword-based queries or simple faceted searches over the dataset metadata. These are insufficient to express information needs that often arise in analytics and modeling, e.g., find data that can enrich analyses, improve a predictive model, or explain outliers in a dataset. We will create a dataset search engine for urban data that supports data-driven and data relationship queries. By enriching the context of the datasets with the analyses, models, and publications that use them, we will support the FAIR principles for urban data.
A key objective of our project is to grow and strengthen a cohesive community around urban computing. We have already assembled a diverse team of 50+ researchers and collaborators that cover several geographical areas in the US and abroad, have expertise in different disciplines, and represent multiple groups of stakeholders. They will use and contribute to the infrastructure. Combined with a concerted outreach effort, our project will have a broad reach.
Connecting data, algorithms, and insights
Collaborating with leading institutions and organizations worldwide
Our collaborative network spans major metropolitan areas including NYC, Chicago, and Seattle, with research partners across multiple continents bringing diverse perspectives to urban computing challenges.
From open-source software development to collaborations with city agencies, our partners drive innovation in sustainable urban infrastructure, transportation systems, and public health analytics.
Stay informed about our latest research breakthroughs and community initiatives
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