USING BIG DATA FOR SUSTAINABLE DEVELOPMENT PURPOSES

In statistical terms, to achieve sustainable development goals, it must provide data according to age, socio-economic characteristics, and residency location to make sure that all social groups, especially the weak ones, have achieved their desired goals.

These statics have to be available locally, not just nationally, and they have to cover all domains and to be continuously updated [6]. This is very found in big data. However, still the weak groups’ problem is there, which prevents achieving these goals simply because these groups do not possess modem technology like the internet and mobiles.

In this context, the statistical committee created the scientific team concerned with using big data for official statics purposes in its 45th session in 2014. The working team is responsible for providing a strategic vision about big data for official statics purposes and directing the program to meet the purposes of indicators designed in the sustainable development plan [7].

In Bogota announcement, it came in “A World Depends on Statics: Harnessing Data Revolution for Sustainable Development Purposes” which recommended using legally these data to produce statics, particularly those measuring the sustainable development indicators:

  • • Using technology, innovation, and analysis to establish a system that includes networks of data innovation to benefit from data, data research.
  • • Capacity building, sources correlated with capacity building, technology transfer, data literacy, and source mobilization through innovative financing mechanisms in partnership with private sectors.

For this, work teams were created in the different fields of data usage: satellite, cell phones, social media means, survey devices, and other teams for developing related skills.

It was also discussed in the UN international Forum on Data hr Dubai (Oct, 22-24, 2018), especially the point of big data and using them in developing real-time data of migration through recorded calls. It also dealt with the attention of raising agricultural productivity using satellite data to identify the fertile lands from the non-ones.

There are many attempts that relied on big data in facing problems; these later are difficult to process with the traditional ways in different sectors for sustainable development, including:

  • • The study of the UN food security program used mobile data to assess food security. The results showed that it is possible to use phone balances as an alternative indicator of the market’s food spending level [8].
  • • Very frequent monitoring data were used in Brazil for calculations related to water.
  • • Satellite images were used in Colombia for mobility and agriculture statics.
  • • Thanks to satellite imaging at night, Sudan was able to complete data related to poverty.

Using big data has allowed identifying the geo-locations extracted from police calls in tracking traffic accidents in Ouagadougou, without a statistical survey, and estimating the deaths and disorders resulting from these accidents [9].

The Global Pulse Initiative is a remarkable initiative that paid attention to big data. It is an innovative initiative of the UN Secretary-General on data sciences. The initiative enhances the awareness of big data opportunities in the sustainable development and the humanitarian work context; it also aims to develop analytical, highly effective solutions and make them available for the United Nations and the Governmental partners through its network of innovative centers of data sciences.

They are Pulse Labs in Jakarta, Indonesia, and Kampala, Uganda, and the United Nations Headquarters in New York. They aim to reduce restrictions that prevent widening the scope and relying on it [10].

21.7 CONCLUSION

Big data are a part of the data revolution, which may improve official statics for achieving sustainable development goals; to fight hunger and poverty, achieving equality, and supporting partnerships.

This is all through the exploitation of different available sources of “data” in terms of quantity, timing, accuracy, and diversity. Therefore, statistical offices should develop their systems in terms of means, techniques, and skills despite what conveys as challenges due to the fast produced data, in return the slow availability of scientific methods in their use, configuration, analysis, and legitimate privacy.

KEYWORDS

  • • big data
  • • data
  • • official statistics
  • • sustainable development

REFERENCES

  • 1. The Commission of Sciences and Technology for Development, (2008). The Commission of Sciences and Technology for Development, www.un.org (accessed on 24 November 2020).
  • 2. www.un.org. (s.d.). (accessed on 22 October 2020).
  • 3. Abu Dhabi Statistics Center, (2013). Available at: www.scad.ae (accessed on 22 October 2020).
  • 4. Ahmed, A. B., (2017). Big Data, its Characteristics, Opportunities, and Strength, http:// www.alfaisal-scientific.com:?p=2093 (accessed on 22 October 2020).
  • 5. https://economie.fgov.be (accessed on 22 October 2020).
  • 6. Cazabat, (2018). The United Nations facing big data: How to use new data sources to optimize the development programs of international organizations. COSSI Journal.
  • 7. Nations, U., (2018). The Economic and Social Council: Using Big Data for the Purposes of Official Statics. The statistical committee.
  • 8. Big Data for Development in Action: The Global Pulse Project Series, UNPG, (2015). Global Pulse Initiative, https://www.unglobalpulse.org/2015/07/big-data-for- development-in-action-the-global-pulse-project-series/ (accessed on 24 November 2020).
  • 9. Bedecarrats, F., & J. C., (2016). Revolution of the Data and Stakes of Statics in Africa, 288.
  • 10. www.onu.org. (s.d.) (accessed on 22 October 2020).

CHAPTER 22

 
Source
< Prev   CONTENTS   Source   Next >