Information Technology: Best Practices and Recommendations SMART Technical Meeting, June 24, 2005 Dennis King US Department of State Humanitarian Information Unit

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Information Technology Best Practices and
Recommendations SMART Technical Meeting, June
24, 2005Dennis KingUS Department of
StateHumanitarian Information Unit
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The Humanitarian Information Unit serves as a US
Government interagency office to identify,
collect, analyze and disseminate unclassified
information critical to USG decision makers and
partners in preparation for and response to
humanitarian emergencies worldwide, and promote
best practices in humanitarian information
management.
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Collaboration and knowledge management

• Humanitarian information comes from a wide
  variety of organizations UN, IOs, governments,
  donors, NGOs, academia
• Humanitarian information comes from a variety of
  sources websites, internal reports, e-mails,
  databases, imagery, media, etc.
• Critical information needs to be continuously
  retrieved, selected, organized and disseminated
  for operational use
• Communities of Interest should be created to make
  critical data and information available to those
  who need it

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Collaboration Tools

• A virtual local area network to share
  data/information regardless of organization or
  location
• All members can upload and download information
  of interest to the community
• Common repository of documents, maps, imagery,
  emails, lessons learned
• Calendar, contact lists, discussion groups, info
  requests
• Health professional community of practice
  collaborate on issues and share information

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Countries of Humanitarian Interest and Concern
CHIC eRoom
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Countries of Humanitarian Interest and Concern
CHIC eRoom
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Critical Humanitarian Information Needs

• Certain critical data/information is always
  needed by decision makers and humanitarian
  organization personnel
• Locating, extracting, filtering and synthesizing
  this information is difficult due to dynamic
  overload of information
• When multi-source data is standardized, it can be
  retrieved, pooled, verified, compared and used
  for analysis

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Data/Text Mining Tools

• Advanced search engines for mining websites and
  databases
• The more standardized the data, the easier it is
  to extract the critical data
• Data/text mining also useful for identifying gaps
  in information

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Data Mining Enter terms, sources, date
perimeters
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Search Results Visualization of number of
matches
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Text Extraction Specific paragraph with words
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Visualization

• Examples Graphs, pie charts, timelines,
  Geographic Information Systems/maps
• Visualization enhances narrative information,
• Visualization facilitates analysis,
  understanding and presents a common operating
  picture

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Geographic Information Systems

• Requires geo-referenced data (lat/longs,
  sub-national administrative areas, baseline
  physical features)
• Permits geo-spatial analysis visualize the
  relationships between humanitarian indicators and
  geography, demography, political/national
  boundaries, etc.
• HIU Project Emergencies Without Borders

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Usual Depiction of Emergencies in Africa, 2003
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Usual Depiction of HIV Prevalence in Africa
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Interpolated HIV Prevalence adjusted for Pop
Density
Interpolated HIV Prevalence model based on more
than 1,200 sentinel surveillance sites that have
reported HIV prevalence among pregnant women.
Multiplying the interpolated HIV prevalence
times the adjusted population distribution
provides a rough estimate of number of people
living with HIV per square kilometer and shows
concentrations of people living with HIV.
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Sample Child Mortality Rates in Africa in 2004
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Sample Child Mortality Rates in Africa in 2004
Country Location lt5 MR Date Source
Angola Ganda -12.9, 14.6 0.9 Sep 2004 ACH-S
Chad Irimi 7.3, 29.1 2.2 Oct. 2004 MSF-B
DRC Kikwit -5.06, 18.8 2.8 Apr 2004 IRC
DRC Mutena -6.3, 20.8 5.2 Apr 2004 IRC
DRC Moba -7.5. 29.7 11.3 Apr 2004 IRC
Somalia Bossasso 11.2, 49.2 2.32 Jul 2004 UNICEF
Somalia Bargal 11.2, 51.0 2.39 Jul 2004 UNICEF
Sudan Kalma camp 13.4, 22.4 11.7 Aug 2004 WHO
Sudan El Geneina 12.5, 24.2 14.1 Jun 2004 MSF/Epicentre
Sudan Aweil (south) 0.7 Jul 2004 MSF/Epicentre
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Areas and Incidents of Conflict and Displacement
In 2004
So Far
in 2005
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Complex Emergency Affected Areas and Refugee
Camps in Africa in 2004
Complex Emergency Affected Areas 2004
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Populations at Risk Information Project

• Aims
• Develop means to improve the estimation and
  management of sub-national demographic
  information for countries with poor or
  unavailable data
• Elevate awareness of this critical information
  need
• Participants
• Department of State, USAID, Census Bureau,
  HHS/CDC, NASA, NOAA, USGS, and others

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Populations at Risk Information Project

• Two parallel activities (August 2005 2006)
• NRC Study The National Research Council of the
  National Academy of Sciences will engage the
  science community to study the use of science and
  technology to better estimate and manage
  sub-national population data.
• Prototype Country Decision Support Packages
  Geographic Information System (GIS)-based models
  developed for Mozambique, Mali, and Haiti will
  provide a basis for exploring the integration and
  application of disparate types and quality of
  information to crises scenarios involving
  climate, conflict, or infectious disease.

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Best Practices

• Dont over-promote the technology/tool,
  demonstrate the use and value with products and
  services
• Emphasize the importance and value of
  standardized data and meta-data (source, date,
  location, etc.)
• Employ visualization to represent complex data,
  display patterns and relationships, and present a
  common operating picture

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Thank You

• Dennis King
• State/INR/GGI/HIU
• Kingdj2_at_state.gov