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Data Disaggregation and Capacity Building for Sustainable Development Goals

This session discusses the importance of evidence-based metrics and data in achieving the UN's 2030 Agenda for Sustainable Development. It focuses on the need for high-quality, timely, and reliable disaggregated data to measure progress and ensure that no one is left behind. The session also explores the role of new technologies in supporting the implementation of the SDGs and the varying technological capacities across countries.

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Data Disaggregation and Capacity Building for Sustainable Development Goals

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  1. UN 2030 Agenda for Sustainable DevelopmentNew Technologies for the SDGsDr. Robert S. ChenDirector and Senior Research Scientist, CIESINThe Earth Institute, Columbia UniversityManager, NASA Socioeconomic Data & Applications CenterCo-chair, Thematic Network on Sustainable Development DataUN Sustainable Development Solutions NetworkApril 23, 2019, Vienna, Austria

  2. Do Evidence, Metrics, and Data Still Matter?

  3. The UN General Assembly Adopted the 2030 Agenda for Sustainable Development in September 2015, including 17 Sustainable Development Goals

  4. Transforming Our World: The 2030 Agenda for Sustainable Development 4. As we embark on this great collective journey, we pledge that no one will be left behind. Recognizing that the dignity of the human person is fundamental, we wish to see the Goals and targets met for all nations and peoples and for all segments of society. And we will endeavour to reach the furthest behind first 48. Indicators are being developed to assist this work. Quality, accessible, timely and reliable disaggregated data will be needed to help with the measurement of progress and to ensure that no one is left behind. Such data is key to decision-making. (emphasis added) https://sustainabledevelopment.un.org/post2015/transformingourworld

  5. SDG Data Disagreggation and Capacity Building 17.18 By 2020, enhance capacity-building support to developing countries, including for least developed countries and small island developing States, to increase significantly the availability of high-quality, timely and reliable data disaggregated by income, gender, age, race, ethnicity, migratory status, disability, geographic location and other characteristics relevant in national contexts 76. We will support developing countries, particularly African countries, least developed countries, small island developing States and landlocked developing countries, in strengthening the capacity of national statistical offices and data systems to ensure access to high-quality, timely, reliable and disaggregated data. We will promote transparent and accountable scaling-up of appropriate public-private cooperation to exploit the contribution to be made by a wide range of data, including earth observation and geospatial information, while ensuring national ownership in supporting and tracking progress. (emphasis added)

  6. Status of SDG Indicators Tier 1: Indicator conceptually clear, established methodology and standards available and data regularly produced by countries. Tier 2: Indicator conceptually clear, established methodology and standards available but data are not regularly produced by countries. Tier 3: Indicator for which there are no established methodology and standards or methodology/standards are being developed/tested. • Inter-Agency and Expert Group on Sustainable Development Goal Indicators (IAEG-SDGs) • Indicators have been categorized into three “tiers” indicating readiness level with respect to implementation. • As of 29 February 2019: 101 Tier I indicators, 84 Tier II indicators, and 41 Tier III indicators; 6 indicators with multiple tiers (21 moved out of Tier III since May 2018) • Many different groups are working to address how indicators can be further developed and implemented, and national capacity developed to support and utilize indicators in sustainable development decision making.

  7. Integrated Approaches to SDG Data and Indicators Are Essential • “The interlinkages and integrated nature of the Sustainable Development Goals are of crucial importance in ensuring that the purpose of the new Agenda is realised. If we realize our ambitions across the full extent of the Agenda, the lives of all will be profoundly improved and our world will be transformed for the better.” (Transforming Our World) • Each SDG needs other SDGs to succeed • Data related to SDGs must therefore be consistent and interoperable Weiss, N. et al. (2014), Cross-sectoral integration in the Sustainable Development Goals: a nexus approach, SEI Discussion Brief.

  8. How Can New Technologies Benefit the 2030 Agenda? • The private sector, academic community, and development organizations are implementing a wide range of “big data” approaches in development • The public sector has the opportunity to “mobilize” the data revolution to more directly support sustainable development.

  9. Technological Capacity Varies Widely • Many National Statistical Offices still using paper forms, outdated computing technology http://www.census.gov/ipc/www/idb/worldpop.html GPM 2014

  10. Recommendations of the 2014 Independent Expert Advisory Group • Develop a global consensus on principles and standards • Share technology and innovations for the common good • New resources for capacity development • Leadership for coordination and mobilisation • Exploit some quick wins on SDG data http://www.undatarevolution.org/wp-content/ uploads/2014/11/A-World-That-Counts.pdf

  11. Cape Town Global Action Plan forSustainable Development Data • Launched in January 2017 by the High-level Group for Partnership, Coordination and Capacity-Building for Statistics for the 2030 Agenda for Sustainable Development (HLG-PCCB) at the UN World Data Forum • Objective 2.3: Facilitate the application of new technologies and new data sources into mainstream statistical activities • Objective 3.4: Integrate geospatial data into statistical production programmes at all levels. • Objective 3.5: Strengthen and expand data on all groups of population to ensure that no(one) is left behind • Objective 3.6: Strengthen and expand dataon domains that are currently not well developed within thescope of official statistics • Objective 5.1:Develop and strengthen partnerships of national and international statistical systems with governments, academia, civil society, private sector and other stakeholders involved in the production and use of data for sustainable development http://undataforum.org/WorldDataForum/wp-content/uploads/2017/01/Cape-Town-Action-Plan-For-Data-Jan2017.pdf

  12. Key Data Challenges – and How Data Science and Technology Can Help Possible Solutions • Improve interoperability of instruments, data systems; smart sensors • Crowd sourcing; on-demand observations; sensor webs; data rescue; new statistical methods • Smarter instruments; validation studies; new statistical methods • New data integration methods; privacy and security improvements; improved technical and legal interoperability • Big data processing; cloud computing; mobile apps and tools • Citizen science/participatory methods; social media; new user interfaces and immersive environments Challenges • Heterogeneous data from diverse sources, instruments • Gaps in data coverage for areas, time periods, vulnerable groups or ecosystems • Highly variable data quality and reliability • Limited capacity to integrate diverse data into useful information and indicators • Lengthy time delays to make usable data available • Insufficient communication and feedback between data providers and users

  13. GI-18 Initiative GEO Has Long Recognized the Potential for EO and Geospatial Data Across the SDGs Alignments of the Goals with specific types of Earth observations and geospatial information

  14. Global Fundamental Geospatial Data Themes • United Nations Committee of Experts on Global Geospatial Information Management (UN-GGIM) • Adopted minimum list of 14 global fundamental geospatial data themes to facilitate measurement, monitoring, and management of sustainable development http://ggim.un.org/meetings/GGIM-committee/8th-Session/documents/E-C20-2018-7-Add_1-Global-fundamental-geospatial-data-themes.pdf

  15. Fundamental Theme:Population Distribution • Population distribution is essential to understanding many of the SDG indicators – both the “numerator” and the “denominator”, i.e.: • Size, location, and characteristics of target populations (e.g., vulnerable groups, people who may be left behind) • Size, location, and characteristics of the underlying population (e.g., for per capita and accessibility indicators) Page 19, http://ggim.un.org/meetings/GGIM-committee/8th-Session/documents/E-C20-2018-7-Add_1-Global-fundamental-geospatial-data-themes.pdf

  16. Fundamental Theme:Buildings & Settlements • Identifying & characterizing settlements and built infrastructure are critical to data gathering (e.g., censuses and surveys), provision of services, managing resources, urban and rural planning, risk management and disaster response, economic applications, etc. • Data are very piecemeal and scattered across different sectors and levels of government • Satellite remote sensing offers potential to develop more consistent assessment of buildings, building characteristics, occupance/usage, and dynamics over time Page 10, http://ggim.un.org/meetings/GGIM-committee/8th-Session/documents/E-C20-2018-7-Add_1-Global-fundamental-geospatial-data-themes.pdf

  17. Night-time lights (DMSP >1 km  VIIRS ~750m) Landsat (~30 m) Radar (~12 m) High resolution imagery(< ~3m resolution) Remote Sensing Key to Mapping Settlements, Infrastructure, and Population in Urban & Rural Areas https://earthobservatory.nasa.gov/images/91044/pinpointing-where-the-lights-went-out-in-puerto-rico https://urban-tep.eo.esa.int/#!pages/dataservices http://ciesin.columbia.edu/data/hrsl/ http://ghslsys.jrc.ec.europa.eu/index.php

  18. Some Challenges in Using These Data for Sustainable Development Monitoring and Applications • Access is scattered; not all open access • Methods not clear; inconsistent documentation, metadata • Some are 1-time, research-oriented products; not updated regularly • Quality may vary by region, time period • No rigorous validation or intercomparison conducted • Not interoperable or well integrated with other related data, e.g., on critical infrastructure, administrative units, water bodies, pop projections

  19. GEO is Taking a Leadership Role • Human Planet Initiative • Co-leads: Martino Pesaresi, JRC; Robert Chen, CIESIN/SEDAC • Range of activities including the Atlas of the Human Planet 2016, 2017, and 2018 • Three NASA-funded HP projects • Human Planet Forum • Entschede, The Netherlands, September 2017 • New York, October 2019 • EO4SDGs • Co-leads: Lawrence Friedl, NASA (US); Chu-Ishida Watanabe, JAXA (Japan); Jose Eduardo De La Torre Barcena, INEGI (Mexico) • Range of projects, capacity building activities, engagement efforts • See: http://eo4sdg.org

  20. POPGRID Data Collaborative:Settlement, Infrastructure, and Population Data Public-private data partnershipinvolving intergovernmental organizations, national & academic research institutions, large and small companies, NGOs, foundations, universities, data stewards, etc.

  21. POPGRID.ORG

  22. Thanks! • Human Planet Forum • Columbia UniversityNYC and Palisades NYOctober 1-3, 2019 • Robert Chenbchen@ciesin.columbia.edu • SDSN TReNDShttp://sdsntrends.org

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