1. 2017 ESIP Summer Meeting Highlights and Next Steps for 3DM
Data Driven Decision Making 3 D M
Karen Moe
ESIP Disasters Lifecycle
Data Driven Decision Making Workshop
Edison Electric Institute, Washington DC
August 3, 2018
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2. Identify and Evaluate Candidate Data Products
Operations personnel submit Use Case (AHC template)
Focus on identifying the problem to be solved and prioritize cases
Resource Movement
Situational Awareness
Damage Assessment
Conduct interviews with key personnel (Duke Energy)
Focus on understanding the Resource Management issues
Identify & Evaluate candidate data products (ESIP, AHC)
Demonstrate capabilities to assess value added to solve problem
Integrate selected products into GeoCollaborate and test in operational exercise
Assess ORL for approved products (AHC)
Operational Readiness Level is associated with data for a selected use case where a process pipeline to SISE can be established
Tentatively identified three areas of interest for candidate data products and services. 
Weather predictions, especially regarding risk of power outages and for deploying resources (trucks, etc) for power recovery operations
Flood map predictions and assessment, especially to support planning the staging and deployment of recovery resources
Infrastructure damage risk and assessment, especially for power lines and poles but also substations

3. Use Case Assessment Session “What’s the right data for this Use Case?”
Analysis of Hurricane Matthew Resource Management issues by Duke Energy
Weather predictions for risk assessments and response planning
Flood maps
Infrastructure damage information
ESIP proposes to explore candidate data sets
Rapid Event Album CollecTions (REACT) from Univ. of Alabama/Huntsville
Tropical Cyclone Information System from NASA Jet Propulsion Laboratory
Dartmouth Flood Observatory
Next steps will examine data set utility, access methods, and operational readiness for specific use cases
Tentatively identified three areas of interest for candidate data products and services. 
Weather predictions, especially regarding risk of power outages and for deploying resources (trucks, etc) for power recovery operations
Flood map predictions and assessment, especially to support planning the staging and deployment of recovery resources
Infrastructure damage risk and assessment, especially for power lines and poles but also substations
Potential candidate data sets that we would like explore and bring forward from ESIP: UAH hurricane event product subscriptions; JPL hurricane prediction model; and UAH drone methodology and products for damage assessment…and possibly a 4th flood prediction product. Offer demos of these products during upcoming AHC (bi-monthly) telecoms.

4. UAH Rapid Event Album CollecTions (REACT)
Event-Driven Data Delivery (ED3) Framework for REACT
° Facilitates planning for data needs
• Improves data preparedness
• Provides reusable framework components
• Supports any event type
• Easy integration of trusted data processes
Provides user subscription services for event-relevant data
● Manages user subscriptions
● Supports definitions of event types
● Supports connection with pre-defined data processes
○ Science Data search/discovery
○ Data product generation/Process workflows
○ Model executions
○ Sensor tasking
○ Relevant social media
● Creation and management of virtual collections (event
albums)
Facilitates planning for data needs
Improves data preparedness
Supports any event type

5. NASA JPL Tropical Cyclone Information System
Fusion of observations and operational model simulations to help improve the understanding and forecasting of hurricane processes. Specifically:
Develop processing techniques to enable multi-source data fusion across hurricane forecast models, satellite data, and in situ sensors.
Develop tools to manage the validation and assessment of model comparisons to more easily evaluate the performance of different numerical models.
Develop interactive visualization techniques to enable analysis of highly complex systems.
Brings models and observations into a common analysis system
Develops on-line analysis tools
Provides interactive visualization of complex storm systems

6. Trusted Data and ORLs Session “What do we mean by Trusted Data?”
Exploration of data quality factors necessary for acceptance and use by the disaster response community
Understanding how users perceive data as trustworthy is key to identifying appropriate data products
End goal is to identify criteria to assess “fitness for use” by disasters operations decision makers
ESIP proposes next steps
Develop criteria for Trusted Data for disaster applications
Get feedback from AHC stakeholder review
Provide trusted data set assessment criteria to guide data set integration steps and help evaluate operational readiness

7. M D 3 2018 ESIP WINTER MEETING Bethesda, MD Bethesda North Marriott
Data Driven Decision Making 3 D M
January 8, 2018 – 3DM Workshop
January 9-11, 2018 – ESIP Meeting
Bethesda, MD
Bethesda North Marriott