BIG DATA IN OFFICIAL STATICS

Official statics that allows the right decision-makings cannot be built except for conect information and complete data. This made the UN adapts “a data revolution” because many developing countries (especially those which have witnessed security crises) lack veiy much the complete, collect data where big data may appear as a complementary alternative for official statics particularly for the fact of modem technology reaching all countries with no exception due to the spread of cell phones.

However, it has to emphasize using census and demographic surveys as the basic data source, considering that it does not prevent the necessity to develop the statistical systems through big data; it cannot be an alternative for traditional research and theories.

This could enhance the database to be comprehensive and integrated, contributing to the quality of demographic estimations and predicting the different demographic phenomena for the right decision-making in demographic planning. It is known that big data are not based on population, so it is necessary to look for ways to adapt them with what serves the demographic objective, especially that they widen the questions about demographic matters and develop the approaches used.

Using big data in official statics proposes many questions: Do big data have the ability to provide the official statistical data in a precise time? Do they have the ability to face the high costs of producing official statistical work and to provide data and indicators with the required accuracy and efficiency? According to the quality norms of statistical data in the national statics offices and the recommendations of official statistical principles [3].

The demographic statics also require personal data of individuals, their social and demographic status, their economic activities, then educational and healthy environment, and their tendencies and behaviors towards demographic matters, which are difficult to be under the privacy frame. For instance, the previous US president Obama with the previous British Prime Minister Cameron asked tech companies (Facebook and Google) to collaborate with intelligence to track terrorists on social media, which provoked human rights organizations for what is called privacy violation [4].

In spite that using big data in official statics remains far from organizations and statistical bodies’ aspirations, but there are leading experiments do not stop on that, and there are many illustrating examples like Estonia, which used mobile-installed tracking devices to improve the touristic statics, and Canada which used GPS devices and Australia which used satellite images for official statistical purposes, whereas in Netherland there are some attempts to use social media means for official statistical purposes too.

Since the UN declaration of ‘Data Revolution,’ it has been monitored many regional and international seminars and conferences to include big data as a new important source of official statics, the most important one was the Paris and Bangkok meetings (April 23-25, 2013) to unite the efforts of statistical organizations in using big data for data production and to make a united system to classify their different types.

At the 59th World Congress of Statics (China, 25-30 August 2013), big data received a wide interest where participants presented some of these data sources like cell phones, energy consumption, electronic payments, and the ways of processing them through cloud computing.

The last was Arabian, the 4th International Conference of Middle East College in big data and Smart Cities (Oman, Jan, 15. 2019).

The aim was to demonstrate the importance of big data and smart cities in improving the living conditions and planning for cities.

According to the UN economic committee’s report, the team is interested in cell phone data for official statics through the partnership between statistical offices and cell phone companies. So it has been the subject where two scientists conducted a work based on analyzing mobile data from 11 countries (EU, Middle East, and Indonesia) using a specific application, preparing, and modeling data by practical examples like applications of typical demographic mobility, migration patterns, transportation, and moving because of diseases and tourism and deleting the population complexes data immediately.

One of the best examples of using big data in official statics is the experience of Belgium. In a comparative study between Belgium census and mobile data extracted from the largest operator there (Proximus) for estimating the demographic density in terms of quality and accuracy that represent an approximate number of inhabitants located in a specific area, where night periods represent a good indicator of residency despite some sort of shortages and mistakes (like having more than one mobile for the same person). It has been found that the correlation coefficient between the density recorded by the census and the one recorded by mobile data equals 0.85 [5]. To access, in the future, better results, it has to develop ways of exploiting mobile data that treat problems they face.

 
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