2018 ESIP Winter Meeting

There is a need to substantiate the benefits of Earth science applications in socially and economically meaningful terms in order to demonstrate return on investment and to prioritize investments across data products, modeling capabilities, and information systems. However, methods and techniques for quantifying the value proposition of Earth observations are currently not fully established. Furthermore, improvements are needed to connect to the decision processes that produce actions with direct societal benefits.

This ESIP session will present a series of case studies that show how U.S. federal and state government agencies are using Earth observations in tandem with ground-based monitors to inform policy decisions. Session speakers include

• Yusuke Kuwayama, Resources for the Future
• Emily Pindilli, U.S. Geological Survey
• Isaac Morrison, Management Systems International

 

The session is organized by the Consortium for the Valuation of Applications Benefits Linked with Earth Science (VALUABLES), a cooperative agreement between Resources for the Future (RFF) and the National Aeronautics and Space Administration (NASA). The VALUABLES Consortium is working to advance methods to value and communicate the applied benefits linked with Earth observations.

Place-based community resilience has emerged as a U.S. national priority with the expectation that it can improve human livelihoods, address environmental change, and prepare communities and households to cope with hazards and disasters (Cutter et al. 2013; NSTC 2014; PCAST 2011). Increased application of Earth Science data for urban and place-based community decision-making can help to inform and enhance social and infrastructural resilience to environmental events and climate change. In this session, we seek to identify specific ways that Earth Science data and the ESIP community can contribute to enhancing place-based community resilience. As our case study for the session, we focus on small- to medium-sized US towns that have city planning staff.

This session builds on previous work conducted at ESIP on community resilience (summer 2015) and integration of multidisciplinary datasets (winter 2017), and current work conducted by the co-organizers on city resilience planning and community development, climate resilience decision-making (Data to Decisions for Climate Resilience ESIP cluster), and capacity-building for stakeholders of city resilience through the use of existing templates.

In this session, we first highlight the data challenges that have been identified in specific cases of U.S. towns that address community resilience issues in their city planning, and architecture, engineering and construction companies that tactically work on the digital infrastructure aspects of city planning. Then, we will introduce some examples of how these challenges may be addressed (e.g., reproducible, traceable, data-driven analytical approaches for integrating societal values and biogeophysical models; emerging technologies for monitoring the environment; indicator datasets; development of templates). We offer some thoughts on how we could realize the value, as well as the cost of not having data, data services, and planning in place to support community resilience.

For the remainder of the session, we lead a discussion with the participants that focuses on: 1) What are potential linkages between data-driven community resilience and other ESIP work, as well as with the overall Earth Science data community?; and 2) What are specific ways that ESIP can contribute specifically to place-based community resilience? We propose that supporting the Earth Science data needs for place-based community resilience and sustainability may be one of the most appropriate spaces for ESIP to direct and emphasize its socioeconomic impact.

The socioeconomic value and benefit of Earth science data, information, and knowledge (DIKW) could be better realized and more evident, when machine-facilitated methods are developed that allow for enhanced discovery and reuse of climate resilience solutions. These solutions are becoming more relevant, as the public becomes increasingly aware of the importance of “decreasing vulnerability by increasing resilience,” one of the objectives of NOAA’s Weather-Ready Nation initiative. The U.S. Climate Resilience Toolkit (US CRT) is an essential resource for documenting climate resilience use cases. The goal of the documentation is to develop a cohesive package of data, tools, and information, so that other communities can re-purpose the solutions contained in those use cases.


This session will explore a number of thought-experiments on “what-ifs,” applied to a hypothetical future version of the US CRT that is enabled by various technologies.
* What if we document traceable resilience solutions as knowledge graphs that can be used by automated reasoners to repurpose a resilience solution for other contexts (e.g., for another location, a related climate stressor, a related climate impact; using related observations, related models, related policy instrument, etc.)?
* What if we crowd-source the contribution of these knowledge graphs with the use of web-based editors that tap into existing ontologies to reduce duplication of concepts?
* What if we design a knowledge graph editor modeled after the Open Science Framework that implements essential open science concepts like attribution, citation, collaboration, unique identifiers, and project forking; from which we could generate metrics to assess the utility of data, information, and applications?
* What if we apply feature-extraction and machine learning algorithms to trawl the ecosystem of climate resilience knowledge graphs, to produce visualizations that could be used to answer user queries? Could the resultant metrics be used by federal agencies to prioritize and justify their investments?
To help guide these thought-experiments, the session will utilize products that have been generated out of the “Data to Decisions for Climate Resilience” and the “Agriculture and Climate” clusters.

You know you can write a great journal paper, and your colleagues assure you that your talks at professional meetings don’t (always) feel like “death by Powerpoint.” However, when you try to communicate the value of your contributions to folks outside your field, you find a lot of them don’t quite get it. If you’re interested in increasing the impact of your science by sharing it with a larger audience, here’s a place to start.

This session will explore some ways to share your science more broadly. We’ll show examples of various tools and trainings available (e.g., AGU’s Kudos(1), AAAS’s Communicating Science Resources(2), and others), look at some engaging examples (e.g., the film Chasing Coral(3), as well as others), and share personal journeys to improved science communication. All levels of experience are welcome; our goal is to help everyone improve.

Tentative agenda:

• Five main science communication goals (LuAnn Dahlman lead)
• Using plain language to broaden your reach (Denise Hills lead)
• Memorable moments: Bridgin the connection between fine arts, liberal arts, and science arts (Christine White lead)

If you'd like your abstract to be used as an example for how to convert a scientific abstract into a plain language summary, please bring it with you to the session, or email it to one of the presentators ahead.

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(1) https://publications.agu.org/files/2017/04/Toolkit-for-authors.pdf
(2) https://www.aaas.org/pes/communicating-science-resources
(3) http://www.chasingcoral.com/

The Disasters Lifecycle cluster is advancing concepts for trusted data for the disasters management community from an end user perspective as contrasted with the science user viewpoint. Work is proceeding on defining Operational Readiness Levels (ORLs) for our ESIP partnership with the All Hazards Consortium. We see ORL assessments as a critical step in bridging the gap between eart science data providers and specific application users. In this session we will explore ways to provide appropriate linkages to existing earth observation repositories with the goal of identifying and tagging metadata with special purpose information such as ORLs.