This post originally appeared on Let's Talk Development.
The World Bank’s classification of economies as low-, lower-middle-, upper-middle-, or high-income has a long history. Over the years these groupings have provided a useful way of summarizing trends across a wide array of development indicators. Although the income classification is sometimes confused with the World Bank’s operational guidelines, which set lending terms and are determined only in part by average income, the classification is provided purely for analytical convenience and has no official status.
This post originally appeared on Let's Talk Development.
You’ll find a large amount of data available through the World Bank’s Open Data Initiative: for time-series alone, there are some 8,000 indicators for around 200 countries. And we’re often asked: “what indicators do you have on topic X, and which should I use?” One way to find your way around is to start at our topical pages. Or, if you have some familiarity with our databases already, look at our full repository of time series data.
Many of you ask what the most popular resources on the open data sites are. I can usually offer a rough answer, but I thought I'd take a moment to respond to the question properly. There's more analysis below, but here's the summary of most popular pages and downloads from the data site:
|Most Popular Pages|
|1||The Indicator, Country and Topic pages|
|2||GDP, GNI and GINI (Inequality) related pages|
|3||The Data Catalog & World Development Indicators page|
|4||Individual country pages: China, USA, India, Brazil, Mexico, Indonesia|
|5||Topic pages: including education, health and poverty|
|6||Economic statistics: goods exports, foreign investment and inflation|
|7||Country income classifications and methodology|
|8||Population, population growth and life expectancy|
|Most Popular Data Downloads|
|1||GDP and GNI Related Data|
|2||World Development Indicators XLS/CSV/PDF|
|3||Country Data: China, USA, India, Brazil, Indonesia|
|4||Foreign Direct Investment & Exports Data|
|7||African Development Indicators|
|8||Country Income Classifications Data|
Is this what you were expecting? Does it correspond with how you use the site?
Are you interested in the accessibility of research, the application of data and the future of development policy? Don't miss these three events happening at the World Bank this week:
- Monday 22nd at 4pm EST: The Kickoff of Open Access Week 2012
- Thursday 25th at 2pm EST: "Turning Big Data into Big Impact"
- Thursday 25th- Friday 26th: "Using History to Inform Development Policy"
If open data is the key to unlocking knowledge and information, then our free, new mobile apps knock down the door.
Family of data, family of apps
The DataFinder apps for iOS and Android use an intuitive interface to present the Bank’s open data for you to explore, analyze and share directly from your smartphone or tablet. The first DataFinder app featured a general selection of data from the World Development Indicators, and today we have new apps focusing on Jobs, Health and Poverty Data. With these apps, you don’t need to be a statistician to navigate charts and maps of development data.
Levels & Trends
in Child Mortality:
Substantial progress has been made towards achieving MDG Goal on Reducing Child Mortality but still insufficient – The new UN-World Bank child mortality estimates
New child mortality estimates (childmortality.org) show that substantial progress has been made towards achieving the fourth Millennium Development Goal. The estimates were released today by the UN Inter-agency Group for Child Mortality Estimation, which includes UNICEF, WHO, the World Bank and United Nations Population Division.
Since 1990 the global under-five mortality rate has dropped 41 percent, from 87 deaths per 1,000 live births in 1990 to 51 in 2011. Four of the six World Bank’s developing regions have reduced their under-five mortality rate by more than 50 percent: East Asia and Pacific, Europe and Central Asia, Latin America and the Caribbean, Middle East and North Africa regions. Progress towards Millennium Development Goal (MDG) 2015 target of a two-thirds reduction is also on track in these four regions. ("On track" indicates that under-five mortality is less than 40 deaths per 1,000 live births in 2011 or that the annual rate of reduction is at least 4 percent over 1990-2011.)
Approximately 50 percent of the global adult population - or 2.5 billion people - are excluded from the formal financial system. Who are the unbanked? The vast majority of these adults are concentrated in the developing world - only a third of South Asians, a quarter of Sub-Saharan Africans, and less than a fifth of Middle-Easterners and North Africans have an account at a formal financial institution (Demirguc-Kunt & Klapper, 2012). Why are these people unbanked? A shortage of money, excessive cost, distance to a bank, and documentation requirements are reported by the unbanked themselves as the main barriers to financial access.
In the World Bank Finances team, we're currently asking ourselves what's next after publishing open financial data? What comes after transparency?
There's of course a lot we still need to do -- we need to help other people publish data (other people's data can make ours even more powerful and help tell more complete stories), we need to help people learn to use our data, we need to raise awareness about the availability and potential of open data, there of course is more (and more granular) data we still need to publish, and the like.
Last month, while World Bank President Jim Yong Kim launched the gender data portal, U.S. Secretary of State Hillary Clinton remarked that “data not only measures progress, it inspires it”. Indeed when data is both relevant and effectively communicated, it can help to inform policies, identify challenges, and catalyze changes and innovations that deliver development results.
With that goal in mind, we started an Open Data Lab. One of our objectives is to help the development community become more effective data communicators by experimenting with different data visualization techniques and tools. The human brain finds it easier to process data and information if it is presented as an image rather than raw numbers or words. And visualizations that let and encourage users to interact with data can deepen their understanding of the information presented.