The use of digital communication technologies, and of mobile phones in particular, has seen an exponential rise in low- and middle-income countries over the last decade. These data, emitted as a byproduct of technologies such as mobile phone location information and calling metadata, have the potential to fill some of the problematic gaps in data resources available to country policymakers and international development organisations. Using three examples of current big data initiatives in the international development field, we examine the implications of these new types of data for development policy and planning: their advantages and drawbacks, emerging practices relating to their use, and how they potentially influence ideas and policies of development. We also assess the politics of these new types of digital data, which are often collected and processed by corporations or by researchers in industrialised countries. Our analysis indicates that these new data sources already represent an important complement to country-level statistics, but that there are currently important challenges which will need to addressed if the promises of big data in development are to be fulfilled.
This is a preview of subscription content, access via your institution.
Buy single article
Instant access to the full article PDF.
Tax calculation will be finalised during checkout.
We use the World Bank’s definitions grouping countries, see: http://data.worldbank.org/about/country-classifications, where LMICs have incomes of $1,036–$12,616 and high income countries (HICS) above that threshhold. Our particular focus is the low- and lower-middle-income countries, with an upper threshhold of $4,085 per capita, which includes India and most of Africa.
Results from the project were presented and discussed in a dedicated session at the NetMob 2013 conference, held at MIT, May 1–3, 2013.
Unusually for this type of mobile phone data study, the researchers took account of the fact that in low-income countries mobile phones are often shared, and calculated the number of people per SIM before extrapolating mobility statistics.
Robert Kirkpatrick, director, UN Global Pulse, in speech to the Internet Governance Forum. Bali, October 23, 2013.
BBC News. (2011). Mobile phones help to target disaster aid, says study. http://www.bbc.co.uk/news/technology-14761144.
Bengtsson, L., Lu, X., Thorson, A., Garfield, R., & von Schreeb, J. (2011). Improved response to disasters and outbreaks by tracking population movements with mobile phone network data: A post-earthquake geospatial study in Haiti. PLoS Medicine, 8(8), e1001083. doi:10.1371/journal.pmed.1001083.
Berdou, E. (2012). Participatory technologies and participatory methodologies: Ways forward for innovative thinking and practice. IKM Working Paper No. 17.
Berlingerio, M., Calabrese, F., Di Lorenzo, G., Nair, R., Pinelli, F., & Sbodio, M. L. (2013). AllAboard: A system for exploring urban mobility and optimizing public transport using cellphone data. In Machine learning and knowledge discovery in databases (pp. 663–666). Berlin: Springer.
Blessing, M. (2005). Het verzet tegen de Volkstelling van 1971. Historische Nieuwsblad nr. 8/2005. http://www.historischnieuwsblad.nl/nl/artikel/6697/het-verzet-tegen-de-volkstelling-van-1971.html.
Blumenstock, J. E. (2012). Inferring patterns of internal migration from mobile phone call records: Evidence from Rwanda. Information Technology for Development, 18(2), 107–125.
Boase, J., & Ling, R. (2013). Measuring mobile phone use: Self-report versus log data. Journal of Computer-Mediated Communication, 18(4), 508–519. doi:10.1111/jcc4.12021.
Borgman, C. (2014). Big data, little data and beyond. Cambridge: MIT Press.
Cavallo, A. (2013). Scraped data and sticky prices. MIT Sloan Working Paper, http://www.mit.edu/~afc/. Accessed 4.10.2013.
Cavallo, A., Cavallo, E., & Rigobon, R. (2013). Prices and supply disruptions during natural disasters. Working Paper 19474, NBER.
Chambers, R. (1997). Whose reality counts? Putting the first last. Intermediate Technology Publications Ltd (ITP).
Collier, P. (2007). The Bottom Billion: Why the Poorest Countries are Failing and What Can Be Done About It. Oxford: Oxford University Press.
Crampton, J. W., Graham, M., Poorthuis, A., Shelton, T., Stephens, M., Wilson, M. W., et al. (2013). Beyond the geotag: Situating ‘big data’and leveraging the potential of the geoweb. Cartography and Geographic Information Science, 40(2), 130–139.
Dandeker, Christopher. (1990). Surveillance, power and modernity. Cambridge: Polity Press.
de Montjoye, Y. A., Hidalgo, C. A., Verleysen, M., & Blondel, V. D. (2013). Unique in the crowd: The privacy bounds of human mobility. Scientific reports, 3.
Donner, Jonathan. (2010). Framing M4D: The utility of continuity and the dual heritage of “mobiles and development”. Electronic Journal on Information Systems in Developing Countries, 44(3), 1–16.
Doron, A., & Jeffrey, R. (2013). The great Indian phone book: How the cheap cell phone changes business, politics, and daily life. London: Hurst&Co.
Eagle, N., & Pentland, A. (2006). Reality mining: Sensing complex social systems. Personal and Ubiquitous Computing, 10(4), 255–268.
Eagle, N., de Montjoye, Y. A., & Bettencourt, L. M. (2009). Community computing: Comparisons between rural and urban societies using mobile phone data. In International conference on computational science and engineering, 2009 (CSE’09) (vol. 4, pp. 144–150), IEEE.
Easterly, W. (2014). The Tyranny of Experts: Economists, Dictators, and the Forgotten Rights of the Poor. New York: Basic Books.
Financial Times. (2013). Argentina: Questioning official inflation can land you in jail. Accessed September 13 http://blogs.ft.com/beyond-brics/2013/09/13/argentina-inflation-diverging-from-official-numbers-can-land-you-in-jail/#axzz2gYghm6jJ.
Frias-Martinez, V., Virseda, J., Rubio, A., & Frias-Martinez, E. (2010). Towards large scale technology impact analyses: Automatic residential localization from mobile phone-call data. In Proceedings of the 4th ACM/IEEE international conference on information and communication technologies and development (p. 11), ACM.
Godard, X. (2003). Urban transport and mobility in African cities. Crisis and inventive disorder. Paper prepared for TRB annual meeting January 2003. http://onlinepubs.trb.org/onlinepubs/archive/am/03-2786.pdf.
González-Bailón, S., Wang, N., Rivero, A., Borge-Holthoefer, J., & Moreno, Y. (2012). Assessing the bias in communication networks sampled from twitter. Available at SSRN 2185134.
Greenleaf, G. (2012). Global data privacy laws: 89 countries, and accelerating. Queen Mary University of London, School of Law Legal Studies Research Paper No. 98/2012.
GSMA. (2013). Sub-Saharan Africa Mobile Economy 2013. http://gsma.com/newsroom/wp-content/uploads/2013/12/GSMA_ME_Sub_Saharan_Africa_ExecSummary_2013.pdf.
Heeks, R., & Kenny, C. (2002). The economics of ICTs and global inequality: Convergence or divergence for developing countries? Development informatics. Working Paper No. 10a, Institute for Development Policy and Management, University of Manchester.
Hildebrandt, M. (2013) Slaves to big data. Or are we? Keynote, 25th June 2013 9th annual conference on internet, Law & Politics (IDP 2013, Barcelona).
ITU. (2013a). The world in 2013. International telecommunications union. http://www.itu.int/en/ITU-D/Statistics/Documents/facts/ICTFactsFigures2013.pdf.
ITU. (2013b). International Internet connectivity in Latin America and the Caribbean. Geneva: International Telecommunications Union.
Jerven, M. (2013). Poor numbers: How we are misled by African development statistics and what to do about it. Ithaca: Cornell University Press.
Keeter, S. (2012). Survey research, its new frontiers, and democracy. Public Opinion Quarterly, 76(3), 600–608.
Kirkpatrick, R. (2011). Data philanthropy: Public and private sector data sharing for global resilience. http://www.unglobalpulse.org/blog/data-philanthropy-public-private-sector-data-sharing-global-resilience.
Klein, N. (2008). The shock doctrine: The rise of disaster capitalism. New York: Metropolitan.
Lane, N. D., Miluzzo, E., Lu, H., Peebles, D., Choudhury, T., & Campbell, A. T. (2010). A survey of mobile phone sensing. IEEE Communications Magazine, 48(9), 140–150.
Licoppe, C. (2004). ‘Connected’ presence: The emergence of a new repertoire for managing social relationships in a changing communication technoscape. Environment and Planning D: Society and Space, 22(1), 135–156.
Ling, R., & Donner, J. (2009). Mobile communication. Cambridge: Polity Press.
Lombard, J. (2006). Enjeux privés dans le transport public d’Abidjan et de Dakar. Géocarrefour, 81(2), 167–174.
Lucas, R. E. (1988). On the mechanics of economic development. Journal of Monetary Economics. 22, 3–42.
Lyon, D. (2007). Surveillance studies: An overview. Cambridge: Polity Press.
Mann, L. (2013). Blogpost on OII’s Policy and Internet Blog: Big Data and Informal Economies in Africa. Accessed 2.10.2013. http://blogs.oii.ox.ac.uk/policy/seeing-like-a-machine-big-data-and-the-challenges-of-measuring-africas-informal-economies/.
Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., et al. (2011). Big data: The next frontier for innovation, competition and productivity. Washington, DC: McKinsey Global Institute.
Musa, P. F., Meso, P., & Mbarika, V. W. (2005). Toward sustainable adoption of technologies for human development in Sub-Saharan Africa: precursors, diagnostics, and prescriptions. Communications of the Association for Information Systems, 15.
NetMob. (2013). Mobile phone data for development: Analysis of mobile phone datasets for the development of Ivory Coast. NetMob conference, May 1–3 2013, MIT, Cambridge, USA.
New York Times. (2000). Who lives here? Who’s asking? In a Black Community, Official Mistrust Hinders Census. Mary 16, 2000. http://www.nytimes.com/2000/05/16/nyregion/who-lives-here-who-s-asking-black-community-official-mistrust-hinders-census.html?pagewanted=all&src=pm.
New York Times. (2011). Haiti: Cellphone tracking helps groups set up more effective aid distribution, study says. http://www.nytimes.com/2011/09/06/health/06global.html?_r=2&scp=1&sq=haiti%20bengtsson&st=cse&pagewanted=all.
Orange. (2012). D4D project. http://www.d4d.orange.com/learn-more.
Reporters Without Borders. (2013). 2013 World Press Freedom Index. http://fr.rsf.org/IMG/pdf/classement_2013_gb-bd.pdf.
Schroeder, R. (2014). Big Data: Towards a more Scientific Social Science and Humanities? In M. Graham, & W. H. Dutton (Eds.), Society and the Internet: How networks of information are changing our lives (pp. 164–176). Oxford: OUP.
Scott, J. C. (1998). Seeing like a state: How certain schemes to improve the human condition have failed. New Haven: Yale University Press.
Schifferes, S., Newman, N., Thurman, N., Corney, D. P. A., Goker, A., & Martin C. (2013) Identifying and verifying news through social media: Developing a user-centred tool for professional journalists. Paper presented at The Future of Journalism Conference, 12–13 September 2013, Cardiff, UK.
Sen, A. (1999). Development as Freedom. Oxford: Oxford University Press.
Taylor, L. (2014). No place to hide? The ethics and analytics of tracking mobility using African mobile phone data. Unpublished paper, University of Amsterdam. http://www.academia.edu/7502204/No_place_to_hide_The_ethics_and_analytics_of_tracking_mobility_using_mobile_phone_data.
Bengtsson, Linus. Director, Flowminder. Interviewed 16.5.2013
Blondel, Vincent. Professor of applied mathematics at the Université Catholique de Louvain and organiser of the D4D challenge. Interviewed 29.3.13
Cavallo, Alberto. Cecil and Ida Green Career Development Assistant Professor of Applied Economics, MIT. Interviewed 15.11.2012
de Cordes, Nicolas. Vice President of Marketing Vision, Orange-France Telecom Group. Interviewed 16.4.2013
Kirkpatrick, Robert. Director, UN Global Pulse. Interviewed 14.5.2013
We gratefully acknowledge funding from the Alfred P. Sloan Foundation for support for the project ‘Accessing and Using Big Data to Advance Social Science Knowledge’ at the Oxford Internet Institute. We are grateful to Ryan Burns and Jim Thatcher for helpful comments on an earlier version, which clarified the paper and improved several points, and to two anonymous reviewers for their comments and ideas.
About this article
Cite this article
Taylor, L., Schroeder, R. Is bigger better? The emergence of big data as a tool for international development policy. GeoJournal 80, 503–518 (2015). https://doi.org/10.1007/s10708-014-9603-5
- Big data