Creating computer simulation systems: an introduction to the high level architecture
Creating computer simulation systems: an introduction to the high level architecture
Clio grows up: from research prototype to industrial tool
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
HePToX: marrying XML and heterogeneity in your P2P databases
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Information integration in the enterprise
Communications of the ACM - Enterprise information integration: and other tools for merging data
The Trident Scientific Workflow Workbench
ESCIENCE '08 Proceedings of the 2008 Fourth IEEE International Conference on eScience
E = MC3: managing uncertain enterprise data in a cluster-computing environment
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Discrete-Event Modeling and Simulation: A Practitioner's Approach
Discrete-Event Modeling and Simulation: A Practitioner's Approach
Communications of the ACM
A dynamical systems model for understanding behavioral interventions for weight loss
SBP'10 Proceedings of the Third international conference on Social Computing, Behavioral Modeling, and Prediction
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As asserted by the Institute of Medicine, sound health policy and investment decisions require use of "what if" simulation models to analyze the potential impacts of alternative decisions on health outcomes. The challenge is that high-level health decisions require understanding complex interactions of diverse systems across many disciplines both inside and outside of healthcare, creating a need for experts across widely different domains to combine their data and models. Splash - the Smarter Planet Platform for Analysis and Simulation of Health - is a novel decision support framework that facilitates combining heterogeneous, pre-existing simulation models and data from different domains and disciplines. Splash leverages and extends data integration, search, and scientific-workflow technologies to permit loose coupling of models via data exchange. This approach avoids the need to enforce universal standards for data and models, thereby facilitating both model interoperability and reuse of models and data that were independently created or curated by different individuals or organizations. In this way Splash can help domain experts from different areas collaborate effectively and efficiently to attack complex health problems. We illustrate Splash's architecture and capabilities using a simple, proof-of-concept model of community obesity. We show how models of transportation, eating habits, food-shopping choices, exercise, and human metabolism can be combined with geographic, store location, and population data to play "what if," asking, for instance, how community obesity measures would change if tax incentives are used to encourage grocery chains selling healthy and inexpensive food to open stores near obesity "hot spots."