Data for Development – contributions from the Nordic countries

OECD is one of the international institutions that makes use of data produced by our use of technology, such as mobile phones and internet, in their research and policymaking (Taylor and Schroeder, 2014, p. 505).

At the end of this month, on October 30th, OECD will release its Development Co-operation Report for 2017, Data for Development. In the introduction of the report, OECD stresses the importance of big data and the data revolution for development in a broad sense: “more and better data can help boost inclusive growth, fight inequalities and combat climate change. These data are also essential to measure and monitor progress against the Sustainable Development Goals.”

Furthermore, the report stresses the fact that the lack of good data is still evident in most developing countries, and asks central questions: Why are over half of deaths and one-third of births worldwide unaccounted for? Why is investment in statistical capacity (…) not a priority for most providers of development assistance?

The report calls for a strengthening of national statistical systems and will present measures to “make data work for development”.

The profiles of different countries’ contributions to data for development is already published. This post briefly looks at the contributions from the Nordic countries in the report: Denmark, Norway, Sweden and Finland.

Denmark
According to the report, more and better data is getting more important than earlier for Denmark when it comes to reporting on the Sustainable Development Goals (SDGs). Until now, it has not been a high priority. Denmark aims to “improve statistical production and promote the use of data by policy makers, civil society and citizens”.

During 2013-2015, Denmark committed on average 12,7 million USD per year to finance statistical capacities and systems in developing countries.

Norway
Norway contributes to strenghtening data for development through its national statistical institute, Statistics Norway. Among other things, Statistics Norway collaborates with the UN’s High Commissioner for Refugees “to establish international guidelines for collecting and producing statistics on refugees and internally displaced people.”

Norway aims to “improve statistical production and data literacy and to strengthen co-ordination among development partners” and it contributes in helping developing countries “to build up civil registration and vital statistics”.

This year, Statistics Norway participated in an expert panel meeting where it provided input to the Development Co-operation report, stressing the importance of building holistic and sustainable national statistical systems (p. 10 in Statistic Norway’s newsletter “International Development Cooperation at Statistics Norway”, June 2017).

Norway launched a white paper this year in where it stresses the importance of good data and statistics in development cooperation.

Norway committed on average 15,0 million USD per year in 2013-15 to finance statistical capacity building.

Countries where Statistics Norway has Institutional Cooperation:

Source: Statistic Norway’s newsletter, June 2017

Sweden
Data for development or building up statistical capacities is an important part of Sweden’s development work. It is included in Sweden’s Budget Bill and the new policy framework for Sweden’s development co-operation. Sweden contributes in improving statistical production and literacy in development countries and offers technical assistance and financial aid. Among other things, it gives financial support to the UN Global Pulse, “which harnesses big data for development and humanitarian action”.

Interestingly, Statistics Sweden has collaborated with Burkina Faso and Mali on establishing “continuous household surveys” to help building up statistical capacity.

Sweden committed on average 20,89 million USD per year to finance statistical capacity in 2013-15.

Finland
The OECD report does not contain any information on Finland’s contribution to data for development. Finland’s contribution this field therefore remains unanswered.

However, Finland contributed a much smaller amount of money than its Nordic neighbours (1,51 million USD per year in 2013-15) to statistical capacity building, which indicates that it is not a priority.

The full country profiles are available here: http://dx.doi.org/10.1787/dcr-2017-en

References:

OECD (2017) Development Co-operation Report 2017: Data for Development, OECD Publishing, Paris. Retrieved 2nd October 2017 from http://dx.doi.org/10.1787/dcr-2017-en

Statistisk sentralbyrå (2017): International Development Cooperation at Statistics Norway: A newsletter from Statistics Norway’s Division for Development Cooperation, June 2017. Retrieved 2nd October 2017 from
https://www.ssb.no/omssb/samarbeid/internasjonalt-utviklingssamarbeid/_attachment/316124?_ts=15d36b4d518

Taylor, L., Schroeder R. (2015): Is bigger better? The emergence of big data as a tool for international development policy. GeoJournal 80: 503-528.

Humanitarian Data in a Development Context

Humanitarian Data in a Development Context
Image Source: Google

Big data is an opportunity for the entire global community to better understand what is happening around us in real time, all over the world. If in 2017 there are more than 7 billion mobile phones in the world, around 6 billion of them are used by people from developing countries. This leads to the production of large amounts of data as these people go about their daily lives.

Using Big Data Safely and Responsibly as a Public Good

Some of the UN Global Pulse initiatives that rely on user generated data online include the following example projects. These demonstrate how big data and mapping techniques are important for both humanitarian action and development:

  • Estimating Socioeconomic Indicators From Mobile Phone Data in Vanuatu. This ongoing project takes into consideration results from recent studies that show that data from mobile phones (Call Details Records and airtime credit purchases) can help in the process of understanding socioeconomic factors where official statistics are absent. The research project uses data from a local telecom operator in Vantau in order to compare if the officially provided statistical data in terms of education and household issues is accurate enough.
  • Exploring the Potential of Mobile Money Transactions to Inform Policy. The project analyses data provided by one of Uganda’s mobile operators to understand if the usage of mobile banking services depends on social networks, time and location. The result of this still ongoing project would help local authorities better understand the decision making process behind these services.
  • Informing governance with social media mining. This project analyzes the first live TV Presidential debates in Uganda in 2016, and it’s direct impact public opinions expressed on Facebook and social media in general. The analysis included 50,000 Facebook posts published publicly during the first two presidential debates on TV. The results of the project confirmed the positive impact of TV debates on democracy in Uganda.

Using Big Data for Mapping Our Future

Haiti in 2010 is considered as the initial moment in digital humanitarianism. And the most used platform for the biggest part of the digital response was Ushahidi. It was created in Kenya to help with tracking the violence after the elections. People used Ushahidi earlier in 2008 so that anyone could send in reports of violence via a web-form or SMS. Then they added the results to a Google map of Kenya (Read, Taithe, Mac Ginty, 2016, p. 9).

By learning from the past and by finding ways to protect the privacy of online users, organizations such as UN Global Pulse already have projects that use the electronically generated data from subscribers around the world. Of course, this data is useful for various purposes. But in most of the cases the gathered data is for creating maps. For example, all over the UN system there are maps. Maps of human rights violations, maps of poverty, maps of crop yields, etc.

In most of the cases, these maps are somehow static and don’t provide 100% reliable data in real time. As Patrick Meier argues, “the radical shift from static, “dead” maps to live, dynamic maps, requires that we reconceptualize the way we think about maps and use them”(Meier 2012, p. 89).

Dodge and Perkins (2009) suggest that “essential to new mapping techniques are imaging technologies, in particular satellite data”. And this results in “radically reshaping the ways different groups comprehend space and place” (Dodge and Perkins 2009, p.497). But they both remind us that “although access to much of this imagery is free, this disguises the powerful interests of corporations such as Google and Microsoft, who produce and own the images and control what we see and thus how we see the world through them” (Dodge and Perkins 2009, p.497).

The Duality of Big Data

In fact, a telecom company is able to track where its users move in real time. And by using this data, it’s possible to create maps of the movements of the population for example. This data can contain information about people going after a disaster, or people going to schools, clinics, etc. Current technology provides methods to create precise maps of people’s behavior in certain situations.

In other words it all depends on how we use and interpret big data. Big data seems to rely on human interpretation. Crawford et al (2013) note that we need to “more broadly consider the human impact – both short and long term – of how data is being gathered and used” (Crawford et al 2013, p. 4.). And “the technologies required to interrogate big data may mean that its use is restricted to a privileged few” (Read, Taithe, Mac Ginty, 2016, p. 11.). Boyd and Crawford argue that big data is ‘a cultural, technological and scholarly phenomenon’ combining technology (advanced computation power and algorithmic accuracy), analysis (identifying patterns to make claims) but also mythology; the belief that it offers new and higher knowledge ‘with the aura of truth, objectivity, and accuracy’ (Read, Taithe, Mac Ginty, 2016, p. 10.)

References

Boyd and Crawford, “Critical Questions,” 663., Last Checked: 1/10/2017, Retrieved from: https://people.cs.kuleuven.be/~bettina.berendt/teaching/ViennaDH15/boyd_crawford_2012.pdf

Crawford, K., Faleiros, G., Luers, A., Meier, P., Perlich, C., and Thorp, J. (2013) Big Data, Communities and Ethical Resilience: A Framework for Action. White Paper for PopTech and RockfellerFoundation. Last Checked 01/10/2017, Retrieved from: https://www.rockefellerfoundation.org/report/big-data-communities-and-ethical-resilience-a-framework-for-action/

Dodge M, Perkins C., The ‘view from nowhere’? Spatial politics and cultural significance of high-resolution satellite imagery. Geoforum. 2009 Jul;40(4):497-501.

Meier, P. 2012: Crisis Mapping in Action: How Open Source Software and Global Volunteer Networks Are Changing the World, One Map at a Time, Journal of Map & Geography Libraries

Read, R., Taithe, B., Mac Ginty, R. 2016: Data hubris? Humanitarian information systems and the mirage of technology, Third World Quarterly, forthcoming. Last Checked: 1/10/2017, Retrieved from: http://dx.doi.org/10.1080/01436597.2015.1136208