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VERSION:2.0
PRODID:unctad.org
BEGIN:VEVENT
UID:6a8d31992f74a
DTSTART:20230425T053000Z
SEQUENCE:0
TRANSP:OPAQUE
DTEND:20230425T063000Z
LOCATION:Hangzhou\, China
SUMMARY:Innovative methods of nowcasting using artificial intelligence\, UN
  World Data Forum 2023
CLASS:PUBLIC
DESCRIPTION:At the mid-point of the time foreseen for enacting the 2030 Age
 nda for Sustainable Development\, there is an urgent need for more timely 
 information for measuring the progress achieved so far and identifying the
  main bottlenecks and areas lagging behind. The COVID-19 crisis put in cle
 ar evidence the importance of timely and granular information for monitori
 ng trends and for guiding the policy responses. However\, many SDG indicat
 ors rely on official data that still suffer from long publication delays o
 r that is only available incompletely or with insufficient coverage. In re
 cent years\, statistical methodologies\, space technologies\, and online d
 ata tools\, including those based on machine learning methods\, satellite 
 remote sensing images\, cloud-end big data platforms\, and new data source
 s have been applied to comprehensively address those information gaps.\n\n
  \n\nUNCTAD co-organizes an event on ways for increasing timeliness and c
 overage of SDG indicators at the 4th UN World Data Forum (24-27 April\, Ha
 ngzhou\, China). The forum will bring together 1 500 in-person and nearly
  20 000 virtual participants from national statistical offices\, internati
 onal organizations\, the geospatial community\, academic organizations\, t
 he private sector\, and civil society organizations to showcase innovation
 s and build impactful partnerships. The Forum is organized under the guida
 nce of the UN Statistical Commission and the High-level Group for Partners
 hip\, Coordination\, and Capacity-Building for Statistics for the 2030 Age
 nda for Sustainable Development\, in close consultation with UN Member Sta
 tes and international partners.\n\nThis session will highlight some recent
  examples of the works utilizing statistical methods and earth observation
  data in relation to specific SDG indicators. Rather than focusing on tech
 nical or computational details\, the panelists will highlight the main cha
 llenges faced when applying their methods/utilities\, as well as solutions
  and lessons learned that could help other actors to continue improving ti
 meliness of SDG indicators at the national and international levels.\n\nDa
 niel Hopp\, Statistician at UNCTAD\, will present innovative methods of no
 wcasting using artificial intelligence. Daniel Hopp has a strong experien
 ce in data ecosystems\, machine learning\, and programming to drive innova
 tion in the domains of trade statistics\, economic forecasting\, and offic
 ial statistics.\n\nSeakers:\n\n\nQunli Han\, Executive Director\, Integrat
 ed Research on Disaster Risk (IRDR) International Programme Office\nHuadon
 g Guo\, Academician &amp\; Director General\, International Research Cente
 r of Big Data for Sustainable Development Goals\nYana Gevorgyan\, Secretar
 iat Director\, Group on Earth Observations (GEO)\nJianhui LI\, Professor\,
  Vice-President\, CODATA of the International Science Council\nGretchen Ka
 lonji\, School of Disaster Reconstruction and Management\, Sichuan Univers
 ity - The Hong Kong Polytechnic University\nDaniel Hopp\, Statistician\, U
 nited Nations Conference on Trade and Development (UNCTAD)\nCharles Brigha
 m\, Geographer\, Esri · Stephen Keppel\, President\, PVBLIC Foundation\n\
 nhttps://unstats.un.org/unsd/undataforum/\n\nView meeting on unctad.org\nh
 ttps://unctad.org/meeting/innovative-methods-nowcasting-using-artificial-i
 ntelligence-un-world-data-forum-2023
DTSTAMP:20260825T060929Z
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