2017 ESIP Winter Meeting: Disaster Cluster Sessions

Notes from 2017 Winter Meeting Disaster Sessions (thanks to Ken Keiser)

Presentations available:
File:Green AGU NRT workshop 11Jan17.pptx (file size: 1.72 MB)
File:Glasscoe et al ESIP Winter 2017 S1.pptx (file size: 1.17 MB)
File:Moran FRWG Stormcenter Ctr Testbed Project Overview 1 11 2017.pptx (file size: 2.68 MB)
File:Bermudez Testbed13-disaster-session.pdf (file size: 6.52 MB)
File:Glasscoe et al ESIP Winter 2017 S2.pptx (file size: 5.5 MB)
File:Keiser Event-based Technologies.pptx‎ (file size: 2.57 MB)

Near Real Time Data for the Disasters Response User Community
2pm Disaster Cluster Session (Karen Moe leading - Dave Jones remote)

Presentation & Discussion with David Green/NASA Applied Science for Disasters
Outcomes of NASA applied science efforts and 2016 workshop on low latency data needs

Addressing need for a timeline of disaster response efforts
Recent workshop on low latency datasets for time-sensitive applications (104 participants)

definitions of near realtime (low latency)
- 0-1 hours (realtime)
- < 3 hours (near realtime)
- 3-24 hrs -
NASA ESD endeavors to provide low latency data when small cost
NASA ESD mission to provide non-real-time data may outweigh near-real-time

NASA Mission support for NRT is secondary and considered as needed
Created an inventory of NRT - lots of datasets. How to identify/search/discover, and usable
Earthdata.nasa.gov - useful for NRT if you know how to use the site, but not so much for others
Recommendations for discoverability were prepared
Establishing a Latency Working Group

focus on use cases - how to address response “workflows”
need for “hazard” datasets (maybe special processing for low-latency datasets)

Questions/Comments

Phil Beilin in CA clearinghouse - how to get involved with latency project?
GSFC (name?) - has similar ideas to help identify relevant datasets for types of event

David looking at how the DAACs can do a better job of providing disaster relevant data

Gary Foley EPA - working with anyone from EPA? - some on ecological hazards - need more links

Presentation by Maggie Glasscoe/JPL - Earthquake activities
Cascadia Rising 2016 - Exercise Timelines and Product Deliveries

Pre-defined events so timeline is known in advance - for purpose of exercise, but not reacting in realtime
FEMA national level exercise - M 9.0 quake in Cascade Subduction Zone
Upcoming Haywired 2017 (USGS) exercise
Timeline of the event - showing when various data sets are available
MSEL - master scenario event list - chronological order of events and injects that drive exercise play

Questions/Comments

Phil Bellin - cross-agency participation
David Green has the cluster been involved with exercises - participants, but not the cluster per se

David - emphasizing participation in exercises - recommended and useful, NASA has a south American exercise planned for later this year

(GSFC) will there be a call for participation in the exercise(s)? Funding available for staging or participating in exercises
Gary Fowler - can we get the data to the onscene coordinators? Important aspect.

Presentation by Tom Moran/AHC (All Hazards Consortium)
Fleet Response Working Group activities with ESIP

Coordination of utility outage response - between 30-120 responding organizations
using Storm Center’s GeoCollaborate application to help organize and expose the data for response
Testbed Project - getting response data to the participants

realtime weather/forecasts
state emergency declarations - must be in trucks to cross state lines
electric sector fleet movement info
live data updates from businesses - worked through liabilities
Open/closed status of private sector businesses (fuel, food, hotels, etc)

Dave Jones comments

evolved from ESIP testbed activity
leading to definition and identification of “trusted” data sources
need better ways to discover the datasets
need to address timeline issues discussed earlier

Improving Resiliency with better data - Data Driven Decision Making (3DM) - workshops

screen sharing approaches - leader/follower approach
private sector owns the technology and allows government participation
exploring NASA (and other) agency data that will be useful - in response to use cases

David Green comments

pick subset of decisions to address - e.g. Haiti earthquake was too complex with too many variables to be a good use case to get good results
consider table-top exercises to learn valuable lessons

Data Driven Decision Making for the Disasters Response User Community
4pm Disaster Cluster Session (Karen leading - Dave Jones remote)

Presentation & Discussion with Erin Robinson/ESIP
ESIP perspectives on the Data Driven Decision Making (3DM) workshop in Oct. 2016

ESIP testbed effort linked up with All Hazards Consortium's Fleet Management Working Group
3DM workshop in Oct - ESIP presence, FEMA, Utility companies - private sector feeling
Hosted at Edison Electric Institute
stakeholders talking about their data needs
ways that ESIP can help bridge the data needs with data available from ESIP members and functions
Dave: in addition to identifying existing datasets is the chance to define new data products

Presentation by Tom Moran/AHC (All Hazards Consortium)
Fleet Response Working Group perspectives on the 3DM workshop

users/decision makers often don’t speak the same language as the data providers
used user “stories” to get across what the data gaps are - identified documentation gaps (declaration of emergency) - problem getting milk to impacted area; problem with turnpike access during an emergency
funding example; $30M for data initiative in 1 state - from 1 utility company
focus on data services - solving problems and use cases
FRWG will probably double in a year
Next workshop last week of Jan in Philadelphia

Questions/Comments

Brian Wee (Neptune) - how is the FRWG structured and participation; SIS (sensitive information sharing) agreement; needed to be private sector run only
Steve Young - potential role of crowd sourcing; WAZE example, not dependable but potentially useful; Haiti efforts led to useful information
David Green - yes, crowd sourcing potential (USGS “did you feel it”); need to get feedback to data producers on the benefit that the data provided - is there a way to get that type of feedback? What difference did it make?

Tom: same concern from private sector - potentially answered by workshops, webinars, etc.

Presentation by Luis Bermudez/OGC (Open Geospatial Consortium)
OGC Testbed plans in 2017

Completed Testbed12

WCS with OPeNDAP
WMS with GIBS
Imagery Quality and Accuracy - digital globe requirements
WPS conflation service
GeoPackage US Topo
Big Data Database
Vector and Raster Tiling
geoJSON user guide
REST user guide

Releasing CFP for Testbed 13 - in January

themes

REST clients
OGC web service interfaces
architecture
semantics - linked data, shared vocabularies, etc
cloud
big data access services
data modeling - dynamic sources

Mass migration - 3d data moving features, 3d portrayal standard, 3d tiles, etc.
Climate change - drought; integration of climate prediction models
Impact of drought on populations; connecting models to social systems

Presentation by Maggie Glasscoe/JPL
Update on Cascadia Rising exercise

providing actionable data for situational awareness
Exercises

Cascadia Rising
Vigilant Guard 17
Haywired 2017

Cascadia Rising

local, state, tribal and federal gov’t joint operation
large number of participants

Vigilant Guard - CA and NV full scale exercise (Nov 2016) - to train, develop and refine joint operations
CA Earthquake Clearinghouse - facilitating field investigations, assist researchers, sharing information, track fieldwork

working on technology interoperability

incident situational awareness sharing
participation with GeoCollaborate ESIP Testbed activity

Presentation by Ken Keiser/UAH
Update on Event-Driven Data Delivery technology

facilitates data preparedness and planning
integration with application such as GeoCollaborate
later session to cover event-based virtual collections

Wrap up by Dave Jones and Karen Moe

Success and results for ESIP Testbed activity
good collaborations of various efforts and projects
plan to follow-up with David Green on South American testbed/exercise
trusted data contribution (below) to Information Quality Cluster - Fostering Collaborations

Presentation by Karen Moe/NASA (Ret.)
ESIP Disasters Lifecycle Cluster and Information Quality

Our key driver for information quality is associated with our goal to define and develop “ESIP-certified” trusted data products to support Data-Driven Decision Making for disasters applications.

Trusted Data concepts (source: tdwi.org)

People use data that they trust, leading to greater consistency, compliance and accuracy in their data-driven processes
People want to feel confident that their data is in the best condition possible because such trusted data makes their jobs easier and their actions more accurate, timely, effective, and compliant (conforming to their requirements).
Trusted data should come from carefully selected sources, be transformed in accordance with data’s intended use, and be delivered in formats and time frames that are appropriate to specific consumers.
Trusted data will meet conditions of completeness, quality, age, schema, profile, and documentation.
From https://tdwi.org/articles/2011/05/18/the-six-cs-of-trusted-data.aspx

Complete – for decision making
Current – freshness, speed of delivery
Consistent – Metadata management can improve consistency by documenting data’s origins and meanings.
Clean – This is typically the result of data quality techniques, such as standardization, verification, matching, and ‘de-duplication’. Users’ perceptions of data quality are probably the biggest challenge to trust, which is why data quality techniques are critical. Quality decisions and operational excellence both depend on clean data.
Compliant – meets required standards (e.g., quality, security, privacy, also federal regulations)
Collaborative – collaboration over data helps ensure that data management and business management goals are aligned.

Trusted Data – some characteristics driving the need for trusted data in disasters applications (ESIP Winter 2016)

Provide actionable information
Sharable / technology interoperability
Common operational data / common view
Sensitive information sharing framework / trusted location
Expedited access

Data-Driven Decision Making defined (ESIP Summer 2016, a sample)

Providing appropriate information for decision makers to enable situational awareness; where appropriate, data is: standardized, simplified, easy to access.
Knowledge-based value added “bundle” of data provided in time for helping to make adequate, timely decisions.
Integrated data & information in easily recognized formats—by the decision makers; easily incorporated in the decision makers’ Common Operation Picture; relevant to the decision makers’ task at hand.
Data-Driven Decision Making is when you use data if expeditious and available, and clearly connected to the problem at hand.

Drivers for the Disasters Response User Community (ESIP Winter 2017)

Need to capture user feedback to measure data usefulness (productivity); OGC is addressing feedback mechanisms
Determine pathway for generating collection level metadata for NASA systematic data
Trust, safety and speed are key drivers for Data-Driven Decision Making