TY - GEN
T1 - Immersive analytics for multi-objective dynamic integrated climate-economy (DICE) models
AU - Simpson, Mark
AU - Wallgrün, Jan Oliver
AU - Klippel, Alexander
AU - Yang, Liping
AU - Garner, Gregory
AU - Keller, Klaus
AU - Oprean, Danielle
AU - Bansal, Saurabh
N1 - Funding Information:
This work was partially supported by the National Science Foundation (NSF) cooperative agreement GEO-1240507 and the Penn State Center for Climate Risk Management and this work was supported by the NSF under IGERT Award #DGE-1144860, Big Data Social Science, and Pennsylvania State University. Funding has also been received through Pennsylvania State University's Institute for Cyber Science. Any conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the funding agencies.
PY - 2016/11/6
Y1 - 2016/11/6
N2 - We are creating an immersive analytics tool for exploring the output of a Dynamic Integrated Climate-Economy (DICE) model, and present early work on the prototype system. DICE models and other Integrated Assessment Models (IAMs) are critical for informing environmental decision making and policy analysis. They often produce complex and multi-layered output, but need to be understood by decision makers who are not experts. We discuss our current and targeted feature set in order to help address this challenge. Additionally, we look ahead to the potential for rigorous evaluation of the system to uncover whether or not it is an improvement over current visualization methods.
AB - We are creating an immersive analytics tool for exploring the output of a Dynamic Integrated Climate-Economy (DICE) model, and present early work on the prototype system. DICE models and other Integrated Assessment Models (IAMs) are critical for informing environmental decision making and policy analysis. They often produce complex and multi-layered output, but need to be understood by decision makers who are not experts. We discuss our current and targeted feature set in order to help address this challenge. Additionally, we look ahead to the potential for rigorous evaluation of the system to uncover whether or not it is an improvement over current visualization methods.
UR - http://www.scopus.com/inward/record.url?scp=85009822969&partnerID=8YFLogxK
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U2 - 10.1145/3009939.3009955
DO - 10.1145/3009939.3009955
M3 - Conference contribution
AN - SCOPUS:85009822969
T3 - Companion Proceedings of the 2016 ACM International Conference on Interactive Surfaces and Spaces: Nature Meets Interactive Surfaces, ISS 2016
SP - 99
EP - 105
BT - Companion Proceedings of the 2016 ACM International Conference on Interactive Surfaces and Spaces
PB - Association for Computing Machinery, Inc
T2 - 11th Annual ACM International Conference on Interactive Surfaces and Spaces, ISS Companion 2016
Y2 - 6 November 2016 through 9 November 2016
ER -