Environmental Resilience Technology: Sustainable Solutions Using Value-Added Analytics in a Changing World

Abstract

Global climate change and associated environmental extremes present a pressing need to understand and predict social–environmental impacts while identifying opportunities for mitigation and adaptation. In support of informing a more resilient future, emerging data analytics technologies can leverage the growing availability of Earth observations from diverse data sources ranging from satellites to sensors to social media. Yet, there remains a need to transition from research for knowledge gain to sustained operational deployment. In this paper, we present a research-to-commercialization (R2C) model and conduct a case study using it to address the wicked wildfire problem through an industry–university partnership. We systematically evaluated 39 different user stories across eight user personas and identified information gaps in public perception and dynamic risk. We discuss utility and challenges in deploying such a model as well as the relevance of the findings from this use case. We find that research-to-commercialization is non-trivial and that academic–industry partnerships can facilitate this process provided there is a clear delineation of (i) intellectual property rights; (ii) technical deliverables that help overcome cultural differences in working styles and reward systems; and (iii) a method to both satisfy open science and protect proprietary information and strategy. The R2C model presented provides a basis for directing solutions-oriented science in support of value-added analytics that can inform a more resilient future.

Keywords

• innovation
• commercialization
• decision making
• human-centered design
• information technology
• data analytics