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SPLASH

SPLASH: Smarter Planet Platform for
                Analysis and Simulation of Health

Project Description

The Smarter Planet Platform for Analysis and Simulation of Health (Splash) is a novel computational framework for integrating independent data, models, and simulations to create comprehensive system models. This supports understanding individual and population health at multiple scales and for multiple purposes.

Health results from complex interactions among many distinct human, environmental, and social systems, such as cultural, educational, political, and economic, as well as policies, practices, organizations, costs, and pricing in industries as diverse as advertising, transportation, agriculture, and others. Interventions and policies aimed at improving population health by affecting one system may have serious and unanticipated consequences in another. Chronic conditions such as obesity have resisted medical, behavioral, and policy interventions that touch a single system. We are not always able to fully think through the interactions among such systems. This is because cross-domain thinking and systems thinking are difficult to do without careful collaboration among experts in different domains to explore complex interdependencies among the operation of the real-world systems. Splash facilitates such cross-domain and systems thinking by supporting collaborations among those with health-related data, models, and problems through an open systems-based platform capable of integrating disparate data, models, and simulations, each representing parts of the broader health system.

The goal of Splash is to facilitate the creation of an interoperating complex composite system model supporting "what-if" analyses by policy makers. Every model is essentially abstracted by a pair of schemas representing, respectively, the format of input data it expects and the format of output data it generates. With such an abstraction at hand, models and data in Splash can be loosely coupled via data exchange. In other words, models and data can be combined together by simply understanding how data can be transformed before it is used by another downstream component model. As a computational platform, Splash supports system-level, model-based collaboration among multiple domain scientists. For science, it aims to raise the collaborative capabilities of experts in biology, medicine, and social sciences working on health-related problems, each using different data, methods, and technologies. For policy, it aims to raise the level of scientific evidence and argument brought to bear on complex health issues, ultimately supporting more effective and less costly health system interventions.

Contact: Paul Maglio

Recent Activites

Splash was presented at:

Publications

Splash Team Members

From left to right: Patricia G. Selinger, Melissa Cefkin, Paul P. Maglio, Peter. J. Haas, Ronald L. Mak, Wang-Chiew Tan, Susanne Glissman, Cheryl A. Kieliszewski, Yinan Li.