Frameworks: Collaborative Proposal: Software Infrastructure for Transformative Urban Sustainability Research

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The United States is highly urbanized with more than 80% of the population residing in cities. Cities draw from and impact natural resources and ecosystems while utilizing vast, expensive infrastructures to meet economic, social, and environmental needs. The National Science Foundation has invested in several strategic research efforts in the area of urban sustainability, all of which generate, collect, and manage large volumes of spatiotemporal data. Voluminous datasets are also made available in domains such as climate, ecology, health, and census. These data can spur exploration of new questions and hypotheses, particularly across traditionally disparate disciplines, and offer unprecedented opportunities for discovery and innovation. However, the data are encoded in diverse formats and managed using a multiplicity of data management frameworks -- all contributing to a break-down of the observational space that inhibits discovery. A scientist must reconcile not only the encoding and storage frameworks, but also negotiate authorizations to access the data. A consequence is that data are locked in institutional silos, each of which represents only a sliver of the observational space. This project, SUSTAIN (Software for Urban Sustainability to Tailor Analyses over Interconnected Networks), facilitates and accelerates discovery by significantly alleviating data-induced inefficiencies. This effort has deep, far-reaching impact. It transforms urban sustainability science by establishing a community of interdisciplinary researchers and catalyzing their collaborative capacity. Hundreds of researchers from over 150 universities are members of our collaborating organizations and will immediately benefit from SUSTAIN. Domains where spatiotemporal phenomena must be analyzed benefit from this innovative research; the partnership with ESRI and Google Earth amplify the impact of SUSTAIN, giving the project a global reach and enabling international collaborative initiatives. The direct engagement with middle school students in computer science and STEM disciplines has well-known benefits and, combined with graduate training, produces a diverse, globally competitive STEM workforce. SUSTAIN targets transformational capabilities for feature space exploration, hypotheses formulation, and model creation and validation over voluminous, high-dimensional spatiotemporal data. These capabilities are deeply aligned with the urban sustainability community's needs, and they address challenges that preclude effective research. SUSTAIN accomplishes these interconnected goals by enabling holistic visibility of the observational space, interactive visualizations of multidimensional information spaces using overlays, fast evaluation of expressive queries tailored to the needs of the discovery process, generation of custom exploratory datasets, and interoperation with diverse analyses software frameworks - all leading to better science. SUSTAIN fosters deep explorations through its transformative visibility of the federated information space. The project reconciles the fragmentation and diversity of siloed data to provide seamless, unprecedented visibility of the information space. A novel aspect of the project's methodology is the innovative use of the Synopsis, a spatiotemporal sketching algorithm that decouples data and information. The methodology extracts and organizes information from the data and uses the information (or sketches of the data) as the basis for explorations. The project also incorporates a novel algorithm for imputations at the sketch level at myriad spatiotemporal scopes. The effort creates a collaborative community of multidisciplinary researchers to build an enduring software infrastructure for urban sustainability.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.