Globally, there are over 98 mobile subscriptions per 100 people, so the chances are, you have a cell phone. Now look at your recent calls, both sent and received: Who do you call most often? Who calls you the most? Do you send, or receive more calls? All this is cell phone metadata: not the content of the calls, but ancillary information, the “who, where and when”.
It’s information that can reveal a lot about you. Your cellphone carrier already uses it to bill you, and may also be using it to target marketing or special offers at you. And with appropriate privacy protections, it can offer researchers a similar opportunity. In this week’s episode of Between 2 Geeks we ask how cellphone metadata (“call detail records”) can help researchers understand entire societies.
The 17 Sustainable Development Goals and their associated 169 targets are ambitious. They will be challenging to implement, and challenging to measure. The Atlas offers the perspective of experts in the World Bank on each of the SDGs.
For example, the interactive treemap below illustrates how the number and distribution of people living in extreme poverty has changed between 1990 and 2013. The reduction in the number of poor in East Asia and Pacific is dramatic, and despite the decline in the Sub-Saharan Africa’s extreme poverty rate to 41 percent in 2013, the region’s population growth means that 389 million people lived on less than $1.90/day in 2013 - 113 million more than in 1990
Note: the light shaded areas in the treemap above represent the largest number of people living in extreme poverty in that country, in a single year, over the period 1990-2013.
Access to information and communication channels empowers women. In 13 countries, women access the internet at a higher rate than men. But this figure represents only one fifth of countries with data - in most the world, women are less likely to be internet users regardless of a country's region or income group.
And if you plot all the countries with available data, we see that in the majority of cases, internet use is lower among women than men.
Facebook recently announced the public release of unprecedentedly high-resolution population maps for Ghana, Haiti, Malawi, South Africa, and Sri Lanka. These maps have been produced jointly by the Facebook Connectivity Lab and the Center for International Earth Science Information Network (CIESIN), and provide data on the distribution of human populations at 30-meter spatial resolution. Facebook conducted this research to inform the development of wireless communication technologies and platforms to bring Internet to the globally unconnected as part of the internet.org initiative.
Figure 1 conveys the spatial resolution of the Facebook dataset, unmatched in its ability to identify settlements. We are looking at approximately a 1 km2 area covering a rural village in Malawi. Previous efforts to map population would have represented this area with only a single grid cell (LandScan), or 100 cells (WorldPop), but Facebook has achieved the highest level of spatial refinement yet, with 900 cells. The blue areas identify the populated pixels in Facebook’s impressive map of the Warm Heart of Africa.
Facebook’s computer vision approach is a very fast method to produce spatially-explicit country-wide population estimates. Using their method, Facebook successfully generated at-scale, high-resolution insights on the distribution of buildings, unmatched by any other remote sensing effort to date. These maps demonstrate the value of artificial intelligence for filling data gaps and creating new datasets, and they could provide a promising complement to household surveys and censuses.
Beginning in March 2016, we started collaborating with Facebook to assess the precision of the maps and explore their potential uses in development efforts. Here, we describe the analyses undertaken to date by the Living Standards Measurement Study (LSMS) team at the World Bank to compare the high-resolution population projections against the ground truth data. Among the countries that were part of the initial release, Malawi was of particular interest for the validation exercise given the range of data at our disposal.
When I speak about big data with government leaders in our client countries around the world, I often find that many have some awareness of big data, but for many, that's where the story ends. Most are not sure how it is going to affect them or what they should do. Most leaders are largely unaware that the impact of big data is likely to be broad and deep. What governments do (or fail to do) will likely shape up the competitiveness of their countries' businesses for the next generation.
In countries further along on its adoption curve, big data has already started to transform not only the information technology sector but almost every business in every industry. Incorporation of big data today is analogous in many ways to the transformative effect of electricity on industries in the 19th century. While electricity production and distribution became an industry in itself, it also led businesses in all sectors to redesign their processes to take advantage of this new resource, leading to unprecedented productivity gains of the Second Industrial Revolution. It isn't surprising therefore that at the recent World Economic Forum in Davos, there was much talk about the global economy being on a brink of a Fourth Industrial Revolution, fueled by big data enabled innovations. Governments in emerging economies cannot afford to be left out of this conversation.
Public Private Partnerships (PPPs) bring together the private sector and governments to provide public infrastructure. The total investment in infrastructure was $25.3 billion in the first half of 2015. The PPP Knowledge Lab brings together data and reports on these projects.
Eight in 10 people in the developing world own a mobile phone, but the cost of using mobiles varies significantly. The 2016 World Development Report explores the impact of the Internet and mobiles on human development.
If you're interested in exploring this data a bit further, I put together a dashboard using the original data source (Table 4.2 in the ITU's Measuring the Information Society 2015 - PDF link). Since extracting data from a PDF isn't always error free, I take responsibility for any "transcription errors" - but having looked it over a couple of times, I don't see anything obviously amiss.
We can all relate to how electronic and electrical equipment (EEE) takes up more and more room in our homes and offices. And as the lifespan of EEE such as computers, smartphones, routers, and monitors shortens, this leads to unsightly piles of barely used, broken, or obsolete equipment.
Eventually these once pricey and “in-demand” EEE get handed over to electronic waste (e-waste) haulers.
The United Nations University (UNU) calculates that about 46 million tons of e-waste was generated globally in 2014, according to a recent study. Although these devices are an essential part of our daily modern life, the societal impact of e-waste can be severe if the e-waste is not managed according to proper waste management standards.
For example, if the e-waste is treated without the necessary care, the e-waste handlers – and in the developing world, this would be working women and children – are exposed to toxic substances.
One of the key policy drivers for Open Data has been to drive economic growth and business innovation. There's a growing amount of evidence and analysis not only for the total potential economic benefit but also for some of the ways in which this is coming about. This evidence is summarised and reviewed in a new World Bank paper published today.