Immersive Analytics for Multi-objective Dynamic Integrated Climate-Economy (DICE) Models

被引：15

作者：

Simpson, Mark ^{[1
]}

Wallgrun, Jan Oliver ^{[1
]}

Klippel, Alexander ^{[1
]}

Yang, Liping ^{[1
]}

Oprean, Danielle ^{[2
]}

Garner, Gregory ^{[3
]}

Keller, Klaus ^{[3
]}

Bansal, Saurabh ^{[4
]}

机构：

[1] Penn State Univ, Dept Geog, University Pk, PA 16802 USA

[2] Penn State Univ, Stuckeman Ctr Design Comp, University Pk, PA 16802 USA

[3] Penn State Univ, Earth & Env Syst Inst, University Pk, PA 16802 USA

[4] Penn State Univ, Smeal Coll Business, University Pk, PA 16802 USA

来源：

COMPANION PROCEEDINGS OF THE 2016 ACM INTERNATIONAL CONFERENCE ON INTERACTIVE SURFACES AND SPACES (ISS 2016) | 2017年

基金：

美国国家科学基金会;

关键词：

immersive analytics; climate change; integrated assessment; evaluation; VIRTUAL-REALITY;

D O I：

10.1145/3009939.3009955

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：99 / 105

页数：7

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