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Barrett, Christopher L.; Johnson, Jeffrey and Marathe, Madhav
(2018).
DOI: https://doi.org/10.1145/3158342
URL: https://ubiquity.acm.org/article.cfm?id=3158342
Abstract
The complexities of social and technological policy domains, such as the economy, the environment, and public health, present challenges that require a new approach to modeling and decision-making. The information required for effective policy and decision making in these complex domains is massive in scale, fine-grained in resolution, and distributed over many data sources. Thus, one of the key challenges in building systems to support policy informatics is information integration. Synthetic information environments (SIEs) present a methodological and technological solution that goes beyond the traditional approaches of systems theory, agent-based simulation, and model federation. An SIE is a multi theory, multi-actor, multi-perspective system that supports continual data uptake, state assessment, decision analysis, and action assignment based on large-scale high-performance computing infrastructures. An SIE allows rapid course-of-action analysis to bound variances in outcomes of policy interventions, which in turn allows the short time-scale planning required in response to emergencies such as epidemic outbreaks.
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About
- Item ORO ID
- 56074
- Item Type
- Journal Item
- Project Funding Details
-
Funded Project Name Project ID Funding Body Data Science Pathways to a re- imagine education 2016-1-IT02-KA203-024645 EC: non-FP non-H2020 European Commission: non-FP (inc.Erasmus) - Academic Unit or School
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Faculty of Science, Technology, Engineering and Mathematics (STEM) > Engineering and Innovation
Faculty of Science, Technology, Engineering and Mathematics (STEM) - Research Group
- Design and Innovation
- Copyright Holders
- © 2018 ACM
- Depositing User
- Jeffrey Johnson