The concept of the Fourth Industrial Revolution (IR4.0) has recently gained a momentum and sparked an increased number of technologies and applications. These IR4.0 technologies have resulted in an increased interest by experts who strive to employ IR4.0 and its applications to meet the needs of institutions and countries. There is no doubt to see the modern technological advancement as a top priority by nations due to the remarkable societal and developmental changes propagated by smart technologies. The term ‘smart’ or ‘intelligence’ is widely used to reflect the proper use of the technological progress in serving the needs of countries and institutions. Nowadays, there are Smart Governments, Industrial Intelligence, Smart Environment, Smart Health, Smart Education and many more of the lifestyles being supported by smart technological tools,
infrastructures and skills, often aimed at optimizing resources to easily achieve the goals and objectives.
When it comes to data science and statistics, we see countries and National Statistics Offices (NSOs) adopt and employ modern methods and tools to shape and develop statistics and data analytics. These modern methods serve and support policymaking, future foresight, prediction, and intervention efforts to improve economic and social development.
The traditional methods of data collection and data analysis alone are not sufficient to meet the ever-growing needs and expectations of policy makers who strive to make effective decisions in a timely manner.
First day registration
Launching ceremony by H.E. Eng. Azza bint Sulaiman Al-Ismaili H.E. Eng. Azza bint Sulaiman Al-Ismaili Minister of Technology and Communications
The Holy Quran
Speech by The General Secretariat of GCC
Majd Abbar - Microsoft Corporation To draw policies and support decision-making, take advantage of the data of the Fourth Industrial Revolution and artificial intelligence techniques to develop official statistics, invest in information wealth and transfer data from just raw data to future visions that help policy-makers and decision-makers
Awarding the winners in the datathon
Launching the exhibition accompanying the forum
Session Moderator: Mohammed Hassan - Federal Competitiveness and Statistics Authority - United Arab Emirates The data transmitted by the sensors installed in the devices of home uses, warehouses, giant containers, speed control devices, imaging devices, water pumps, electric generators, and others related to the World Wide Web (the internet). Requiring of these resources by the statistical and information centres produce statistical indicators such as the volume of electricity and water consumption, road accidents and logistical statistics.
Internet of Things and Official Statistics, What is the Barrier?. Marc Debusschere- Statistics Office -Belgium
Big data and uses of the Internet of Things (11: 00-10: 45) Khaled Mostafa - Oracle Corporation Traffic indicators using road sensor data (11: 15-11: 00) Dr.Aziz Al-Juaid - General Authority for Statistics - Kingdom of Saudi Arabia Using big data in the statistics and information sector (11: 30-11: 15). Ahmed Al-Mafraji - National Center for Statistics and Information - Sultanate of Oman The smart solution to the irrecoverable data of official statistics (11: 45-11: 30) Riva Rufiadi - Central Statistical Organization - Indonesia
Session Moderator: Maha Abdullah Sabt - Information and e-Government Authority - Kingdom of Bahrain
It is the data that is formed on social networks through the exchange of dialogue between users on various topics and participation, and the exchange of views between the public on topics and issues of public opinion. This information has had a direct and indirect impact on decision-making.
These sources have become providing enormous information, from which primary statistical and informational indicators can be extracted, and benefit in what is known as early warning and others.
Electronic payment information and credit cards It is the data produced in huge quantities through the uses of credit cards and electronic payment in commercial transactions such as buying and selling. From these sources, it is possible to produce statistical indicators on purchasing power, household and individual consumption, and other economic indicators for statistical and information centres.
Artificial intelligence to take advantage of the data of the World Wide Web of social media information. Varun Khandelwal - Bahwan Cybertek Emirates
Statistical indicators from web data (12: 15-12: 30) Dr. Aseel Al-Mansour - General Authority for Statistics - Kingdom of Saudi Arabia Job vacancies as data source SURS experiences in web scraping for statistics (12:30-12:45) Tomaz Speh - Statistical office – Slovenia Electronic payment information and credit cards (12:45-13:00) Latifa Al Shehhi - Federal Competitiveness and Statistics Authority - United Arab Emirates Twitter mood in Mexico (13: 00-13: 15) Silvia Frasto - National Institute of Statistics and Geography - Mexico
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A summary of the first day
Session Moderator: dr. Aseel Al-Mansour - General Authority for Statistics - Kingdom of Saudi Arabia
It is the data that is driven from administrative procedures and institutional systems represented in the process of registering transactions and requesting multiple and different services in the public and private sectors. These sources may produce data and statistical information that provide the necessary statistical and informational indicators in place of relying on internal statistical sources such as censuses and field surveys.
Accessibility statistics from non- traditional data sources to meet the needs of customers . Pasi Veikko Piela - Statistics Office - Finland
Remote Sensing Data (09:25-09:40) Mohammad Hassan - Federal Competitiveness And Statistics Authority- United Arab Emirates Using algorithms to find urban growth and population estimates(09:40-09:55) Olivia Jimena -National Institute of Statistics and Geography- Mexico Land degradation project summary .(09:55-10:10) Malik Al-Wardy-Ministry of Environment and Climate Affairs- Sultanate of Oman
Session Moderator: Mohammed Al-Mohannadi - Planning and Statistics Authority - Qatar It is the data that is driven from administrative procedures and institutional systems represented in the process of registering transactions and requesting multiple and different services in the public and private sectors. These sources may produce data and statistical information that provide the necessary statistical and informational indicators in place of relying on internal statistical sources such as censuses and field surveys.
Administrative data in the age of smart statistics, opportunities and challenges. Nancy Elizabeth - GCC-Stat
Using administrative records to produce official statistics (11:00-1115) Maha Sabt -Information and e-government authority- kingdom of Bahrain Use of log data and its impact on statistical releases(11:15:11:30) Hawra Mohammed - Central Statistical Bureau- Kuwait Evaluation of administrative records for statistical use(11:30-11:45)Elham Salih- GCC-Stat
Session Moderator: Dr. Jamil bin Darwish Al-Shaqsi - Sultan Qaboos University Augmented analytics is the use of statistical and linguistic technologies to improve data management performance, from data analysis to data sharing and business intelligence. It is somehow connected to transform big data into smaller, more usable, datasets. Depending on multiple related disciplines such as (computer science and statistics) extracting knowledge to look ahead.
A journey toward artificial intelligence in institutions Dr. Ahmed El-Sayed - IBM
Deeper insights and faster decision making with GIS and AI (12:15-12:30). Linda Peters- Esri- America Big Data Evolution in Government & Enterprise Sectors(12:30-12:45) . Mohammed Hassanien - Omantel- Sultanate of Oman A journey toward artificial intelligence in institutions(12:45-13:00) Ahmad El Sayed - IBM Data Governance Application Strategy(13:00-13:15) Jaffar Al-Khaboori- Oredoo- Oman
A word by His Excellency / Saber bin Saeed Al Harbi, Director General of the Statistical Center for the Cooperation Council for the Arab Gulf States
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