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Webinar on ‘Big Data Applications and Utilising Non-Traditional Data Sources and Methods for Official Statistics’
 
Date : 10 June 2021 Venue : Virtual-SESRIC, Ankara Turkey

Within the framework of its Webinar Series on Statistical Experience Sharing, SESRIC organised a webinar on ‘Big Data Applications and Utilising Non-Traditional Data Sources and Methods for Official Statistics’ in collaboration with National Statistical Offices (NSOs) of Indonesia, Jordan, Malaysia, Oman, Saudi Arabia, Turkey, and the Statistics Division of the United Nations Economic and Social Commission for Western Asia (UNESCWA) on 10 June 2021 with the participation of 60 attendees from the NSOs of 17 OIC countries and 2 international organisations.

The objective of the webinar was to share experiences in the development and/or use of big data applications and utilising non-traditional data sources and methods for official statistics.

The webinar covered the following topics:

  • Opportunities and challenges of using non-traditional data sources, particularly big data, for official statistics; and
  • Concrete big data applications of the OIC countries including the use of non-traditional data sources and methods such as satellite imagery data, mobile phone data, scanner data, Automated Identification System (AIS) vessel tracking data, earth observation data, machine learning, and others.

The webinar was conducted through a video conferencing platform by following synchronous learning and instruction approaches designed in line with the virtual training solutions undertaken by SESRIC in order to better serve the Centre’s training activities and keep participants motivated and engaged during this time of global crisis due to COVID-19.

Documents:

  • Concept Note (English)
  • Experience of Indonesia in Developing Big Data for Official Statistics, BPS-Statistics Indonesia (English)
  • ESCWA’s Contribution to Regional Geospatial Data for SDGs-Environment Indicators and Disaster Risk Management, UNESCWA (English)
  • Leveraging Big Data and Non-traditional Data for Policy Effectiveness Evaluation during COVID-19 Pandemic, Department of Statistics of Jordan (English)
  • Price Intelligence (PI) – Data Gathering by Utilizing Web Crawling, Department of Statistics Malaysia (English)
  • Oman’s Experience in Utilizing Mobile Positioning Data for Official Statistics, National Centre for Statistics and Information of Oman (English)
  • Using Employment Data and Comparing it with Unemployment in Various Indicators, General Authority of Statistics of Saudi Arabia (English)
  • Big Data Applications in TurkStat, Turkish Statistical Institute (English)
  • Big Data for Public Policy and Decision Making, UNESCWA (English)
  • Collecting Price Data through Web Scrapping, UNESCWA (English)

Photos

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