2017 ESIP Winter Meeting: Disaster Cluster Sessions

From Earth Science Information Partners (ESIP)

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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)


  • 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


  • 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


  • 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

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