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III. Big Data: App for Health, Natural Resources, and Environment Session 3 Workshop 02/14/2020 1 Group (A/B) Participants for BIG DATA APP FOR HEALTH, ENVIRONMENT AND NATURAL RESOURCES Overall Group Leader: Dr. Zita VJ. Albacea GROUP MEMBERS (A/B) 1. NEDA Carlos Bernardo O. Abad Santos 9. Project NOAH - Ken Aracan 2. DepEd Marieta C. Atienza 10. Geodata Elaine Ocampo

3. DOST-ICTO Maria Teresa M. Garcia 11. World Bank Sharon Faye Piza 4. NAMRIA Rosal Dolanas 12. PSA Josie B. Perez 5. DENR Lolita Presbitero 13. PSA Vivian R. Ilarina 6. DENR Liberty Fernandez 14. PSA Reynor R. Imperial 7. PPPC Yna Mari Isobel Alihan 15. PSA Bernadette B. Balamban 8. UPLB INSTAT Ronald R. Roldan

16. PSA Wilma Guillen 02/14/2020 2 The FOCUS GROUP OBJECTIVE Gather key points for developing principles that will kick-start and motivate interest in collaborative approaches using BIG DATA. Recommendations will be made on the following: BIG DATA FOR HEALTH, NATURAL RESOURCES AND ENVIRONMENT engagement/partnership arrangement between statistical offices/systems and other providers and sources of data improvements in the national statistical system to leverage use of big data in official statistics 02/14/2020 3 Low Hanging Fruits. What forms of BIG DATA can already be used to generate national statistics (eg SDG indicators) on health, environment and natural resources Health

Clinical Data Admin-based data (e.g. FHSIS) Pharmacy transactions (manually recorded purchases) Health insurance (digitized) Hospital Statistical Reports Civil Registry - Vital Statistics Disease Registry data Environment Sensors data weather data water level sensors Air and Water Pollution monitoring Topographic data

Natural Resources Data gathered from LAWIN Project (data on trees and biodiversity) National Greening Program (NGP) Satellite Images NAMRIA hydrographic data 02/14/2020 4 DATA GAPS. Which data gaps on health, environment and natural resources can be addressed by the use of big data? Value propositions for each segment or product/service Health MMR and other mortality ratios Statistics on PWDs Disaggregation variables

of IMRs Private Clinic Data Responsiveness of health services providers (non medical health) Out of pocket health expenditure Disaggregated data Data on HIV Environment Biodiversity data as required by SDGs Coastal resource data Flora and fauna Data on protected areas Annual Land cover data Natural Resources Data on Renewable

Energies Fossil fuels disaggregation of data Carbon emission 02/14/2020 5 Ethics and Principles. Are there overarching principles in the use of BIG DATA for HEALTH, ENVIRONMENT, NATURAL RESOURCES? Suggest the most important ones. Health

Environment Privacy/ Confidentiality Trade secrets Data Coverage Representativeness Data Quality Confidentiality on mining companies Security of data Data Coverage Data Restrictions Natural Resources Data Coverage Data Restrictions 02/14/2020 6

What Makes BIG DATA Sell : Environment Overall Value Propositions for Health, Natural Resources, Yesterday, several Value Propositions make BIG DATA very attractive NEW SOURCES of actionable data: cheap, real time, disaster mitigating, etc. Thinking of stakeholders, please suggest others that are immediately useful and actionable. Data Gap filler Alternative basis for policy analysis Participato ry Can be used for Validation

Increased efficiency Enhanced partnership and collaboration 02/14/2020 7 Design a LEARNING COMMUNITY Describe/design a workable Learning Community (or Committees or R&D Teams) needed for Incubation-to-Launch & Performance or Quality Benchmarking Activities for a multi-sectoral Big Data initiative for the Philippines. The output of this multi-sector collaboration will be nothing less than a vibrant ecosystem feeding big data inputs for the benefit of stakeholders. Existing Sectoral IACs Add representative from the private sectors, CSOs, and technical researchers 02/14/2020

8 Business Model LEARNING COMMUNITY Output Name top 3 accomplishments for this LEARNING COMMUNITY. 1. Data assessment with priority to SDG indicators 2. Standards 3. Developed expertise Suggest 3 PILOT PROJECTS (At least 1 leading to an SDG Indicator). 4. Advocacies on Big Data to High Level Officials 5. Conducting workshops, trainings, and FGDs 6. Developing a data architecture and a standardized system for encoding of manually-inputted data 02/14/2020 9 Failsafes for Business MODEL LEARNING COMMUNITY In what ways can this LEARNING COMMUNITY fly high (or fail)? High Level Champion Cooperation

Human and financial resources 02/14/2020 10 Executive Summary (Group Leader to highlight key points; may get additional inputs assistance from raconteurs, moderator, and PSA staff) 02/14/2020 11 Thank you For additional inputs please email moderator in time for final report preparation until June 25, 2016 eob: Nicco de Jesus - [email protected] 02/14/2020 12

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