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Centralized Warehouse to
synergize sporadic data sources
for efficient emergency response
Janak Parajuli, Survey Officer, Survey
Department, Nepal
Suman Baral, GIS-Database Expert,
Habitat for Humanity Nepal
11/25/2019 1
How the idea conceived?
11/25/2019 2
about the topic
We do have data
information and
insight available in
scientific
community,
Government and
non-government
organizations,
private institutions
Available in the
form of paper,
journals models,
social media,
websites, API and
other freely
available
databases
These all
resources could be
synchronized into a
standard format
with proper
communication and
dissemination
channel
During disasters it
serves for quick
response
11/25/2019 3
From 2005-2015, 7,00,000 lost
their lives due to different disasters
worldwide
In the last seven years, more than
12,000 lost their lives in Nepal
From 2005-2015, 1.4 million people
injured 24 million people homeless
1 dollar invested in resilient
infrastructure could save 7 dollars
in response and recovery cost
why it’s important?
11/25/2019 4
Sendai Framework for
Disaster Risk Reduction
(2015-2030)
11/25/2019 5
It is the storage location of processed historical and current information
and for this context should be based on four priorities of Sendai framework
• Understanding disaster risk
• Strengthening Disaster Risk Governance
• Investing in disaster risk reduction for resilience
• Importance of disaster preparedness for effective response and to Build
Back Better in recovery, rehabilitation and reconstruction.
using data mining functions (associations, clustering, séquence rules,
classifications etc.)
Data Warehouse (DWH)
11/25/2019 6
working methodology
Before emergency During emergency
Data from different sources like
RS imageries, UAVs, social
media, GIS Databases, research
and academia reports etc.
Processed through Extract
Transform Load (ETL) and inserted
into data warehouse
Visualizing information in
dashboards in the form of reports
with the aid of data mining functions
Supporting response plan
following core humanitarian
principles
Implementation in the
field based on Sphere
standards
11/25/2019 7
Implementation
Connecting affected population to response activities
through program design, implementation and evaluation for
• Saving lives
• Reducing injuries and
• Lessening property loss
to improve situation awareness
11/25/2019 8
Thank you
Together we can
11/25/2019 9

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Centralized Warehouse to synergize sporadic data sources for efficient emergency response

  • 1. Centralized Warehouse to synergize sporadic data sources for efficient emergency response Janak Parajuli, Survey Officer, Survey Department, Nepal Suman Baral, GIS-Database Expert, Habitat for Humanity Nepal 11/25/2019 1
  • 2. How the idea conceived? 11/25/2019 2
  • 3. about the topic We do have data information and insight available in scientific community, Government and non-government organizations, private institutions Available in the form of paper, journals models, social media, websites, API and other freely available databases These all resources could be synchronized into a standard format with proper communication and dissemination channel During disasters it serves for quick response 11/25/2019 3
  • 4. From 2005-2015, 7,00,000 lost their lives due to different disasters worldwide In the last seven years, more than 12,000 lost their lives in Nepal From 2005-2015, 1.4 million people injured 24 million people homeless 1 dollar invested in resilient infrastructure could save 7 dollars in response and recovery cost why it’s important? 11/25/2019 4
  • 5. Sendai Framework for Disaster Risk Reduction (2015-2030) 11/25/2019 5
  • 6. It is the storage location of processed historical and current information and for this context should be based on four priorities of Sendai framework • Understanding disaster risk • Strengthening Disaster Risk Governance • Investing in disaster risk reduction for resilience • Importance of disaster preparedness for effective response and to Build Back Better in recovery, rehabilitation and reconstruction. using data mining functions (associations, clustering, séquence rules, classifications etc.) Data Warehouse (DWH) 11/25/2019 6
  • 7. working methodology Before emergency During emergency Data from different sources like RS imageries, UAVs, social media, GIS Databases, research and academia reports etc. Processed through Extract Transform Load (ETL) and inserted into data warehouse Visualizing information in dashboards in the form of reports with the aid of data mining functions Supporting response plan following core humanitarian principles Implementation in the field based on Sphere standards 11/25/2019 7
  • 8. Implementation Connecting affected population to response activities through program design, implementation and evaluation for • Saving lives • Reducing injuries and • Lessening property loss to improve situation awareness 11/25/2019 8
  • 9. Thank you Together we can 11/25/2019 9

Editor's Notes

  1. Portals and Android applications for data collection developed during research assistantship at KU…when we involved in rescue operations, found everything havoc and mismanaged…victims not getting relief materials…had there been some sort of central data warehouse, the scenario would have been different…
  2. Even a number of research papers presented here at this conference have collected data from different sources.
  3. Worldwide:- UN OCHA Nepal: DRR portal, Ministry of Home affairs
  4. Sendai Framework was adopted at the Third UN World Conference on Disaster Risk Reduction in Sendai, Japan, on March 18, 2015. Four priorities and seven targets of disaster risk reduction. Sphere Standards: The Sphere Standards were created by a Red Cross and Red Crescent movement in collaboration with volunteers of NGOs. It also claims that the philosophy of Sphere resides on two main beliefs: • Every people who are affected by disaster have right to life and assistance with self-respect. • Necessary precautions and steps ought to be taken to lessen human suffering due to disaster.
  5. Associations: finds items in your data that frequently occur together in the same transactions. Classification: with the Classification algorithms, you can create, validate, or test classification models. For example, you can analyze why a certain classification was made, or you can predict a classification for new data. Clustering: searches the input data for characteristics that frequently occur in common. It groups the input data into clusters. The members of each cluster have similar properties. Sequence rules: The Sequence Rules mining function finds typical sequences of events in your data.
  6. Response Plan: the figures of injured, casualties and missing ones. Similarly, the number of internally displaced people (IDP) can be determined to calculate the required count and apposite location of evacuation camps and shelter. Besides, it will be very easy to supply food, medicine and relief materials also Core humanitarian principles: humanity, neutrality, impartiality and independence Sphere Standards: four vital response areas which are i. Health ii. Food Security and Nutrition iii. Shelter and Settlement and iv. Water Supply, Sanitation and Hygiene Promotion (WASH)
  7. Standing order on disaster: who does what, defined responsibilities