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Iscram Summer School 2009   From Mashups To Modelling (Tom De Groeve)
 

Iscram Summer School 2009 From Mashups To Modelling (Tom De Groeve)

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Large catastrophes often trigger international humanitarian response. This is a particular context in which many independent actors, including governmental agencies (e.g. search and rescue teams), ...

Large catastrophes often trigger international humanitarian response. This is a particular context in which many independent actors, including governmental agencies (e.g. search and rescue teams), non-governmental organizations (NGO’s such as Doctors Without Borders), corporations (e.g. Google or Microsoft) and international organizations (including the United Nations Office for Coordination of Humanitarian Affairs) work together to provide first response and subsequent relief and reconstruction assistance. In the absence of a clear command and control structure, situational awareness needs to be acquired by each actor independently. Needless to say that this community is eager to develop and use technology and systems to acquire and share information, and that collaboration and information sharing is generally considered as mutually benefitting.
In the early onset of disasters, information is sparse. Traditionally, there are three main sources of information: scientific monitoring systems (e.g. seismological or meteorological networks), official information (briefings by the local emergency management agency) and media reports. Information management for each source requires different technological solutions, respectively focused on modelling, web portals for information sharing, and linguistic processing. However, more recently a fourth source of information is becoming available through Web 2.0: information from citizens, sometimes labelled crowd-sourcing. In case of a disaster, local (and remote) citizens can and do provide information (e.g. eyewitness reports) or analysis (e.g. compiling reports in an information feed). However, this fourth source is not widely used yet by emergency managers because the reliability of the information is not well understood and hard to assess in a time-critical environment.

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    Iscram Summer School 2009   From Mashups To Modelling (Tom De Groeve) Iscram Summer School 2009 From Mashups To Modelling (Tom De Groeve) Presentation Transcript

    • From mash-ups to modelling:
      technology for international crisis situation awareness
      ISCRAM Summer School 2009
      Tom De Groeve – tom.de-groeve@jrc.ec.europa.eu
      Joint Research Centre of the European Commission
      27 August 2009
      ISCRAM Summer School 2009, Tilburg
    • ISCRAM Summer School 2009, Tilburg
      European Commission
      European Commission
      Directorates General (per policy area)
      Humanitarian Aid (DG ECHO)
      External Relations (DG RELEX)
      Environment and Civil Protection (DG ENV)
      Research (DG JRC)
      Research policy and funding (DG RTD)
      Development aid (DG DEV, DG AIDCO)

      Directorate General Joint Research Center
      7 institutes (per research area)
      2500 staff
      Institute for the Protection and the Security of the Citizen
      IT, Engineering, Statistics, Geomatics
      Global Security and Crisis Management
    • ISCRAM Summer School 2009, Tilburg
      European Commission
      European Commission is a large player in international disaster management
      Policy and action for disasters
      Humanitarian aid office (ECHO):
      largest humanitarian aid donor in the world
      Civil Protection Mechanism
      Coordination of European first response
      Monitoring and Information Center (MIC)
      External Relations:
      Prevention, mitigation, reconstruction programmes
      Development:
      Reduction of vulnerability and improvement of resilience
      Humanitarian aid
      Civil Protection Mechanism
      Reconstruction
    • European Commission
      Role of the European Commission
      Principle of subsidiarity
      Need for specific mandate at European level
      Intermediary between multilateral organisations and EU Member States
      European institutions
      European Council
      Heads of state
      European Parliament
      European Court of justice
      European agencies
      European Centre for Disease Control
      ISCRAM Summer School 2009, Tilburg
      Multilateral org’s
      European Commission
      EU Member states
    • European Commission
      Natural disasters
      ISCRAM Summer School 2009, Tilburg
      Affected
      government
      Assessment
      UNDAC
      Response
      OCHA
      Response org
      (e.g. NGO, IFRC)
      Funding
      Coordination
      ECHO (funding)
      EC Monitoring and
      Information Centre
      EU Member state
      Search & Rescue
    • European Commission
      Health
      ISCRAM Summer School 2009, Tilburg
      WHO
      Data aggregation
      ECDC
      Coordination
      European Commission
      DG SANCO
      Surveillance
      Policy making
      EU Member state
    • Lecture overview
      International situation rooms
      Information management roles, capabilities and needs
      Detection, analysis, briefing, action
      Information management tools
      Mash-ups versus Spatial Data Infrastructure
      Access, analyze and share information
      Information modelling
      Make information work for your business processes
      ISCRAM Summer School 2009, Tilburg
    • Part 1
      International Situation Rooms
      Roles, capabilities and needs
      ISCRAM Summer School 2009, Tilburg
    • International situation rooms
      European Institutions
      ECHO: humanitarian aid
      Humanitarian aid funding
      Civil Protection Mechanism (MIC)
      International search and rescue
      Cross-border European disasters
      Multi-lateral assistance
      External Relations (RELEX)
      Community level foreign affairs
      Reconstruction after war or disaster
      European Council
      Political foreign affairs response
      Health (SANCO)
      Epidemic control measures
      Border control (FRONTEX)
      Border monitoring
      NATO
      African Union
      World Bank
      United Nations
      Office for Coordination of Humanitarian Affairs
      Sudden onset response coordination
      UNDAC: disaster assessment
      World Food Program
      Early warning for food crises
      Response to food crises
      Peacekeeping Operations
      Pre or post conflict
      World Health Organisation
      Pandemics
      International Non Governmental Org’s
      International Federation of Red Cross
      National (non) governmental org’s
      Urban Search and Rescue: USAR.nl
      Italian Civil Protection
      ISCRAM Summer School 2009, Tilburg
    • International situation rooms
      Roles
      Primarily an advisory role, rather than an operational role
      Information processing for situational awareness and political response.
      Wide Scope
      Geographically: continental or global
      Thematically (any kind of crisis)
      Tasks
      (Support) rapid decisions for sudden onset disasters or crises
      Regular briefs on slow onset or continuous crises
      Staff
      Generalists or specialists in response
      Experience in decision making, less in information management
      Small number of staff, rarely working in 24h shifts
      Information
      No access to intelligence information
      Sometimes access to private network of experts (delegations, regional offices, roster of experts)
      Operation
      Not much routine because of the variety of crisis situations
      No or little standard operating procedures
      ISCRAM Summer School 2009, Tilburg
    • ExampleGlobal Disaster Alert and Coordination Systemwww. .org
      an example of a disaster alert and impact system for international humanitarian assistance
      ISCRAM Summer School 2009, Tilburg
    • International humanitarian aid
      A complex system with many stakeholders
      No “Command and Control Centre”
      Help is based on scarce information on the disaster
      What, when, how, who?
      Decisions must be made very quickly (within 72h)
      ISCRAM Summer School 2009, Tilburg
      Coordination: UN OCHA
      Humanitarian Aid Flow
      Donors
      ECHO, etc.
      Charity
      UN
      WFP,HCR…
      Int. NGOs
      IFRC, MsF
      Local
      Government
      Local
      NGOs
      Victims
    • Inefficiencies in humanitarian response
      Monitoring disasters
      24/7 monitoring capacity is expensive
      Many heterogeneous sources of natural hazard monitoring  hard to keep up to date
      Response can be delayed because
      Not alerted / monitored
      Affected government does not appeal
      Not sure if others respond
      Size and type of response must be needs driven (Madrid Declaration 1995)
      Size of disaster can be under/overestimated
      Information on needs can be incomplete, vague, lacking
      ISCRAM Summer School 2009, Tilburg
      Is it a disaster??
      How many people??
      What are the needs??
      Who will respond??
      What is offered??
      What is needed now??
      What is the damage??
      time
    • Visit to NERSS, 29-30 July 2009
      12 May 2008, 6:41 UTC
      14 minutes after earthquake
      4500 emails, 2700 SMSs and 100 faxes sent to first responders globally
      Department of Earthquake Disaster Emergency Management
      Red earthquake alert: “high likelihood of a disaster, with need for international assistance”
      Global Disaster Alert and Coordination System
    • Visit to NERSS, 29-30 July 2009
      M 6.7
      M 6.0
      “Is an event of humanitarian concern?”
      The objective is to distinguish between
      large earthquake in unpopulated or resilient regions
      smaller earthquake in highly populated and vulnerable regions
    • Visit to NERSS, 29-30 July 2009
    • Visit to NERSS, 29-30 July 2009
    • Visit to NERSS, 29-30 July 2009
      Cyclone category IV
      7 million people with high winds
      1.8 million in storm surge zone
      Cyclone category I
      No people affected
    • Visit to NERSS, 29-30 July 2009
    • Visit to NERSS, 29-30 July 2009
      Prior to GDACS: monitoring through bookmarking
    • Visit to NERSS, 29-30 July 2009
      With GDACS: One-stop-shop
      Information standards; added-value systems; System of systems
    • Source of situational information
      Example:
      international humanitarian sudden-onset disaster
      OCHA system
      Where can we find information?
      ISCRAM Summer School 2009, Tilburg
    • Sources of situational information
      Early warning and alert systems
      Timely knowledge about the occurrence of a natural hazard
      Geophysical, meteorological measurement systems
      Automated consequence analysis
      Modelling the likely impact
      International and social media
      Rich source, very timely
      but not always true and complete
      ISCRAM Summer School 2009, Tilburg
    • Sources of situational information
      Office for Coordination of Humanitarian Affairs (UN-OCHA):
      Mandate to coordinate humanitarian response
      Sends disaster assessment and coordination (UNDAC) teams, search and rescue teams (through the INSARAG network)
      Sets up an On Site Operations Coordination Centre (OSOCC), humanitarian information centres (HIC)
      Disseminates all information through ReliefWeb
      Local government, with its local emergency management authority (LEMA):
      Main source for official information on the scale of the disaster
      ISCRAM Summer School 2009, Tilburg
    • Sources of situational information
      Alert systems
      Consequence Analysis Tools
      Media
      UN-OCHA
      Local Emergency Management Agency
      ISCRAM Summer School 2009, Tilburg
      Reliability
      Timeliness
    • Information needs versus sources
      ISCRAM Summer School 2009, Tilburg
      Early warning or alert
      Automated consequence analysis
      Media
      OCHA
      LEMA
      Situation
      Source contains information for need
      X
    • Information needs versus sources
      ISCRAM Summer School 2009, Tilburg
      Need clusters
      Source contains information for need
      X
    • Scope and mandate
      ISCRAM Summer School 2009, Tilburg
      Health
      Response
      Political
      IFRC
      Civil Protection
      UNDPKO
      Humanitarian
      NATO
      WFP
      Action
      WHO
      SANCO
      RELEX
      Policy
      Funding
      ECHO
      European Council
      Sudden onset
      Slow onset
      Time scale
    • Scope and mandate
      ISCRAM Summer School 2009, Tilburg
      Health
      Political
      NATO
      WFP
      Humanitarian
      20
      IFRC
      UNDPKO
      Staff
      10
      European Council
      RELEX
      Civil Protection
      5
      ECHO
      SANCO
      National
      Global
      Regional
      Time scale
    • Responsibilities
      ISCRAM Summer School 2009, Tilburg
      Monitoring
      Declare crisis
      Briefing on state of the world
      Briefing on crisis (strategic)
      Gather info for action (tactical)
      Action
      Decision
    • Responsibilities
      ISCRAM Summer School 2009, Tilburg
    • Capabilities
      ISCRAM Summer School 2009, Tilburg
    • Monitoring
      ISCRAM Summer School 2009, Tilburg
    • Briefing on State of the World
      ISCRAM Summer School 2009, Tilburg
    • Declare disaster
      ISCRAM Summer School 2009, Tilburg
    • Briefing on disaster (strategic)
      ISCRAM Summer School 2009, Tilburg
    • Gather info for action (tactical)
      ISCRAM Summer School 2009, Tilburg
    • Roles and capabilities in local response
      ISCRAM Summer School 2009, Tilburg
      Offensive
      Pre-emptive
      Exploitative
      9
      8
      3
      2
      7
      1
      Before
      After
      4
      6
      10
      5
      8
      11
      9
      Protective
      Corrective
      Defensive
      From Bharosa, Janssen (2009)
    • International situation rooms
      Responsibilities
      Capabilities
      ISCRAM Summer School 2009, Tilburg
      Monitoring
      Detect
      Evaluate relevance
      Declare crisis
      Briefing on state of the world
      Map
      Get data
      Analyze
      Brief
      Briefing on crisis (strategic)
      Gather info for action (tactical)
      Communicate
      Share
      Collaborate
      Action
      Decision
    • Part 2
      Geospatial information management tools
      Mash-up versus Spatial Data Infrastructure
      ISCRAM Summer School 2009, Tilburg
    • Mash-up
      Mash-up
      Combination of different web services
      Combination of data and functionality
      API: application programming interface
      Mostly map based
      GeoRSS, KML: geotagged data
      JavaScript
      Examples of APIs
      Google maps
      Google geocoding
      Bing
      Panoramio: photos

      Create your own
      http://www.programmableweb.com/howto
      http://www.wayfaring.com
      ISCRAM Summer School 2009, Tilburg
    • Examples of mash-ups
      Healthmap.org
      ISCRAM Summer School 2009, Tilburg
    • Examples of mash-ups
      Reuters AlertNet
      ISCRAM Summer School 2009, Tilburg
    • Examples of mash-ups
      Hungarian Emergency and Disaster Information Service
      Pandemic map
      ISCRAM Summer School 2009, Tilburg
    • Examples of mash-ups
      Hungarian Emergency and Disaster Information Service
      Pandemic map
      ISCRAM Summer School 2009, Tilburg
    • Examples of mash-ups
      Ithaca
      ISCRAM Summer School 2009, Tilburg
    • Examples of data sources
      ISCRAM Summer School 2009, Tilburg
    • Examples of data sources
      ISCRAM Summer School 2009, Tilburg
    • Spatial Data Infrastructure
      Professional GIS system
      Database technology to store and process geospatial data
      Handles topology, projections, attributes, metadata, long transactions, conflict resolution
      Visualization powerful on desktop
      Functionality can exposed as web services
      Good for
      Data creation
      Data editing and maintenance
      Data analysis
      Map creation
      Not so good for
      Web-based interactive maps
      Handling non-GIS data formats (e.g. KML, GeoRSS)
      ISCRAM Summer School 2009, Tilburg
    • Spatial Data Infrastructure
      GIS = Geographic information system (or science)
      Mapping
      ISCRAM Summer School 2009, Tilburg
    • GIS
      Handling, storing geospatial data
      Coordinate in 2D or 3D space
       special database techniques
      Spatial Reference System  projection
      Imagery  large volumes of data
      Most (>80%) data has geospatial component
      Manipulating, querying geospatial data
      Nearby point, line, polygon
      “In” area, “intersecting” with line
      Raster statistics  sum of population in pixels
      ISCRAM Summer School 2009, Tilburg
    • Visit to NERSS, 29-30 July 2009
      Rubble(pink)
      Standing buildings(red)
      Built up structures (red)
      Automatic damage assessment using textural analysis
    • GIS systems: network enabled
      Web mapping
      Web querying
      Web processing
      Routing
      Nearest objects
      GIS Model
      ISCRAM Summer School 2009, Tilburg
      My system
    • ISCRAM Summer School 2009, Tilburg
    • SDI based systems
      ISCRAM Summer School 2009, Tilburg
    • What’s needed in the situation room?
      ISCRAM Summer School 2009, Tilburg
    • Data
      ISCRAM Summer School 2009, Tilburg
      Mash-up
      Own base map
      Own data
      Traditional SDI
      Other base maps
      Other data
      Mash-up
      Unusual
    • Co-visualize information
      ISCRAM Summer School 2009, Tilburg
    • Best available map
      ISCRAM Summer School 2009, Tilburg
    • What’s in my area of interest
      ISCRAM Summer School 2009, Tilburg
    • What’s in my area of interest
      ISCRAM Summer School 2009, Tilburg
    • Functionality
      ISCRAM Summer School 2009, Tilburg
      SDI
      Mash-up
      Data creation
      Data analysis
      Data visualization
      International situation room
    • Model output; support RSS/KML
      ISCRAM Summer School 2009, Tilburg
    • What’s happening here?
      ISCRAM Summer School 2009, Tilburg
    • Advanced mash-up
      ISCRAM Summer School 2009, Tilburg
    • Mash-up or SDI?
      Without mash-up?
      Dynamic information streams cannot be used
      Web 2.0 data not useful
      Missing out on lots of new developments, APIs and tools
      Rigid desktop visualization
      Without SDI?
      No advanced modelling
      Own data can not be stored or displayed
      Dependent on commercial base maps
      Can’t create or digitize data
      Dependent on network availability and information service providers
      ISCRAM Summer School 2009, Tilburg
    • Part 3
      Information modelling
      Mash-up versus modelling
      ISCRAM Summer School 2009, Tilburg
    • Modelling
      Case studies
      Impact modelling: GDACS
      Media mining: EMM
      ISCRAM Summer School 2009, Tilburg
    • Modelling
      Combination of information to obtain more useful information
      Make use of available information to estimate/calculate useful information
      Mathematical, physical, statistical
      Quantitative or qualitative
      Examples
      Likelihood for need for international humanitarian intervention after a natural disaster
      Tsunami wave height at coast given an earthquake
      Breaking news
      Filter and cluster information
      ISCRAM Summer School 2009, Tilburg
    • Visit to NERSS, 29-30 July 2009
      GDACS automatic and manual event analysis
      Alert
      Coordination
      Volcano
      Monitoring
      Networks
      Disaster
      Level II Alert
      Disaster
      Level I Alert
      Earthquake
      Observation
      Networks
      Automatic Evaluation of scale of disaster
      Manual Evaluation of scale of disaster
      Event Alerts
      Start of coordi-nation
      Flood
      Watch
      Networks
      Trop. Cyclone
      Observation
      Networks
      Geographical,
      Socio-economic, population data
      Eye witness and information from Local
      Government, IFRC, ECHO, NGO
      Models
    • Visit to NERSS, 29-30 July 2009
      Disaster alert: systematic impact analysis
      Risk analysis
      Risk = Hazard x Population x Vulnerability
      Hazard = 0 then Risk = 0
      Population = 0 then Risk = 0
      Vulnerability = 0 then Risk = 0
      Impact analysis is similar
      Impact = Event magnitude x Population in affected area x Vulnerability
      Volcano
      Monitoring
      Networks
      Earthquake
      Observation
      Networks
      Flood
      Watch
      Networks
      Trop. Cyclone
      Observation
      Networks
      tsunami
      earthquake
      Socio-economic Indicators (e.g. UNDP, World Bank)
      Landscan or GPW
    • Earthquake mechanism
      Plate tectonics
      Relative motion of plates
      ISCRAM Summer School 2009
      Terminology
      Hypocentre and epicentre (on surface)
      Magnitude: logarithmic measure of energy
      Intensity: energy on surface at given distance from epicentre
    • Earthquake mechanism
      Energy propagates
      P and S waves
      Attenuation functions
      Depends on local geology
      ISCRAM Summer School 2009
      Energy shakes buildings
      Earthquake engineering
      Vulnerability curves
    • Earthquake occurrence
      Earthquakes, each year
      500 000 detectable
      100 000 can be felt
      100 cause damage
      ISCRAM Summer School 2009
    • Earthquake effects
      Shaking and ground rupture
      damage to buildings or other rigid structures.
      Site or local amplification (Mexico City effect):
      transfer of the seismic motion from hard deep soils to soft superficial soils
      Landslides and avalanches
      ISCRAM Summer School 2009
      Soil liquefaction
      water-saturated granular material temporally loses their strength and transforms from a solid to a liquid
      buildings or bridges tilt or sink into the liquefied deposits
      Tsunamis
      Fires
      break of the electrical power or gas lines
    • Earthquake data
      Occurrence
      Near real time (<15 min)
      Location and magnitude, with uncertainty
      USGS NEIC (US)
      EMSC (Europe)
      GEOFON (Germany)
      JMA (Japan)

      ISCRAM Summer School 2009
      Propagation
      Shakemaps (USGS)
      ESRC (Russia)
      Missing datasets
      Building stock
      Location, number, type of buildings
      Localized attenuation functions
    • GDACS earthquake alert system
      Scraping of earthquake parameters
      Agreements with seismological institutes
      US National Earthquake Information Center (NEIC)
      European Mediterranean Seismological Centre (EMSC)
      Japanese Meteorological Agency (JMA)
      Indonesia, Germany, France, Italy…
      Calculation of impact
      Population in 100km
      Landscan dataset
      Cities
      Critical infrastructure nearby
      Nuclear plants
      Hydrodams database not complete (e.g. in China)
      Airports
      Secondary effects
      Landslides
      Tsunamis
      Logistics
      Airport capacity nearby
      Visit to NERSS, 29-30 July 2009
    • Earthquake alert system
      Reporting
      Multi-lingual reports: English, French, Spanish, Italian, Turkish, Chinese
      Full, dynamic web report
      Short static email report
      Fax report (PDF)
      SMS message
      (Voice messages)
      Creation fully automatic, based on templates
      Alerting
      Professional SMS provider
      200 SMS/second
      Global coverage
      Professional Fax, Voice providers
      Over 10000 users
      Alert logic
      Green, Orange, Red
      Regional filter
      No cancellation; only new alert if alert level increases
      Visit to NERSS, 29-30 July 2009
    • Visit to NERSS, 29-30 July 2009
      The JRC Tsunami Early Warning System
      After the 2004 Tsunami in Banda Aceh, Indonesia, JRC decided to include Tsunami models for a quick evaluation of the possible impact of a Tsunami as a consequence of an earthquake
    • Visit to NERSS, 29-30 July 2009
      The JRC Tsunami Early Warning System
      Timeline:
      December 2004: no Tsunami model, only earthquake alerts
      March 2005: rough estimation of Tsunami probability, Travel time model
      October 2006:
      SWAN-JRC Model for height distribution and locations identification
      International Tsunami Workshop, Ispra 5-6 October
      March 2007: full integration of the Tsunami model in GDACS
      August 2007: start of the grid calculations for over 30000 tsunami scenarios
      March 2008: integration of matrix calculations in GDACS
      JRC Models:
      Travel Time model – March 2005
      SWAN-JRC Model – October 2006
      Tsunami Grid system – March 2008
    • Visit to NERSS, 29-30 July 2009
      Model characteristics
      fast running
      reliable unbreakable
      automatically activated on request (web service)
      integrated in the GDACS
      Based on the integration of the shallow water propagation speed
      Similar to the x-ray technique
      Provides the time in each point, starting from a source
      Run-time: 20 seconds
      -60
      20
      8
      JRC Travel Time model
    • Visit to NERSS, 29-30 July 2009
      SWAN-JRC Tsunami Model
      Automatic calculation of wave generation and propagation to the coast
      Triggered by GDACS
      Automatic fault generation
      Direction, length, height
      Based on initial earthquake parameters (lat/lon/magnitude)
      Wave propagation
      SWAN code (C. Mader) rewritten in C language for faster processing
      Post processing:
      List of affected cities (with wave height)
      The code does not calculate the run-up to the coast
      much finer bathymetry is necessary
      not relevant for early warning
      Run-time: 20 minutes
      Indonesia Magnitude 8.4
      12 September 2007 11:10 UTC
      Major locations identified:
      Kandan, 3.3 m
      Belowa, 2.7 m
      Pandangaget, 1.9 m
    • Visit to NERSS, 29-30 July 2009
      Tsunami Grid
      Historical epicenter
      Bounding box
      (Ring n. 0)
      Ring n. 1
      Ring n. 2
      For early warning, 20 minutes is too long.
      Pre-calculation of scenarios
      10143 tsunami sources
      grid around historical Tsunami events (from the NOAA Tsunami sources database)
      10x10 grid of 0.5 degrees around each data point
      13 calculations per point
      magnitude from 6.5 to 9.5 every 0.25
      131856 calculations
      2 TB space
    • Visit to NERSS, 29-30 July 2009
      Tsunami Grid
      10184 data points in a grid of 0.5 degrees
    • Integration in GDACS
      GDACS tsunami alert
      Logic:
      earthquake in sea,
      magnitude > 6.5
      Look up tsunami scenario, and associated maximum wave height
      If wave height > 3: Red alert
      If wave height > 1.5: Orange
      Otherwise: Green
      Take maximum of earthquake and tsunami alert
      Reduction of false tsunami alerts by 90%
      Tsunami Analysis Tool
      Combine
      Real-time sea surface buoy data
      Tsunami scenarios
      Earthquake monitoring
      New tsunami calculations
      Allows to confirm tsunamis, based on buoy data
      Visit to NERSS, 29-30 July 2009
    • GDACS
      Impact calculation allows to filter important events from unimportant ones
      Uses well-chosen information feeds, from sensor networks
      Provides information feed of high (or known) quality
      Visit to NERSS, 29-30 July 2009
    • But don’t underestimate crowd-sourcing
      USGS uses information collected from local people through the web to adjust their shaking models
      Visit to NERSS, 29-30 July 2009
    • But don’t underestimate crowd-sourcing
      EMSC does the same
      And uses hit peaks as a confirmation of a strong earthquake
      Visit to NERSS, 29-30 July 2009
    • But don’t underestimate crowd-sourcing
      Network of hard disk sensors
      Network of iPhone or Andoid phones
      Visit to NERSS, 29-30 July 2009
    • Visit to NERSS, 29-30 July 2009
    • Europe Media Monitor
      What is the News Brief?
      Summary of news stories from around the world, automatically classified according to thousands of criteria. It is updated every 10 minutes, 24 hours a day.
      "Top Stories" automatically detects the stories that are the most reported in each language at the moment.
      Search: previous news stories (over 20 million articles are indexed).
      How does it work?
      Generated automatically by software algorithms without any human intervention.
      alert definition consists of a list of multilingual keywords
      What info is extracted?
      Clustering
      Geotagging, place names
      Named entities: people, organizations, titles, functions
      Quotes
      Related clusters in other languages; in time
      Visit to NERSS, 29-30 July 2009
    • Event detection
      Visit to NERSS, 29-30 July 2009
    • What is MedISys?
      MedISys (Medical Information System) is a real-time news alert system for medical and health-related topics.
      MedISys:
      processes over 20000 articles per day from over 4000 sites of approximately 1600 news sources (news and medical sites) in 45 languages,
      dynamically updates statistics on all news topics every 10 minutes,
      categorises articles in pre-defined medical topics in 25 different languages,
      How does it work?
      MedISys turns news into a signal. Over time stories come into the news then gradually disappear. Some topics appear regularly whereas other topics occur infrequently. MedISys keeps track of these topics comparing current news events with those in the past in order to quickly identify breaking news.
      What does MedISys offer over other news providers?
      The system uses dynamic statistical modelling techniques to:
      suppress news noise, i.e. stories that are regularly in the news,
      enhance stories with a poor signal, and
      identify individual events on a temporal and locational basis.
      Visit to NERSS, 29-30 July 2009
    • Visit to NERSS, 29-30 July 2009
    • Visit to NERSS, 29-30 July 2009
    • Mash-up versus modelling
      Visit to NERSS, 29-30 July 2009
      Modelling
      Mash-up
      Quality
      Trust
      Customized
      Quantity
      Flexibility
      General
      International situation room