[Esip-agclimate] Reminder: Ag & Climate Call Tomorrow

DAVIS, ELEANOR J eleanord at email.sc.edu
Mon Apr 27 17:15:07 EDT 2020

The ag and climate cluster will host an introductory webinar on a nascent data-to-decisions experiment on Tuesday 2020-04-28 | 3 PM  EDT. GotoMeeting details are listed in the ESIP meetings calendar.

To join the meeting from your computer, tablet or smartphone, click:

You can also dial in using your phone.

United States: +1 (224) 501-3412

Access Code: 534-768-669

What this is about:
In the 2020 Collaboration Area Highlights webinar, the Ag and Climate Cluster outlined a nascent experiment to capture the knowledge of subject matter experts across science, technology, and policy areas in the form of use-cases documented as concept maps. The intent is to build these use-cases on a common "backbone" of risk management with a focus on climate adaptation and mitigation against the impacts of extreme events.

Ultimately, we anticipate that these concept maps will be used for communication, engagement, and (hopefully) machine-assisted context-aware discovery of data, information, and knowledge.

If you are interested in topics like US policies relevant to large-scale environmental change, modeling tools used for characterizing the anticipated impacts of extreme weather in light of adaptation challenges, or telling the story of how a data product you developed is connected to resilience planning, the ag and climate cluster will host an introductory webinar on this data-to-decisions experiment on Tuesday 2020-04-28 | 1500 hrs EDT

This webinar will be based on a presentation at our ag and climate telecon on 2020-04-07 and updated with ideas from subsequent discussions to (hopefully) include the skeletal structure of an in-development risk management use-case centered on wildfires and flooding. This new use-case is hung off the same risk management backbone which is also used for an existing use-case on climate adaptation for poultry agriculture in the Chesapeake watershed.

(IMPORTANT QUALIFIER: even though the use-cases are based on actual real-world challenges, none of the use-cases are "complete" in this experiment.)

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