There’s a range of studies that suggest that the potential prize from Open Data could be enormous - including an estimate of $3-5 trillion a year globally from McKinsey Global Institute and an estimate of $13 trillion cumulative over the next 5 years in the G20 countries. There are supporting studies of the value of Open Data to certain sectors in certain countries - for instance $20 billion a year to Agriculture in the US - and of the value of key datasets such as geospatial data. All these support the conclusion that the economic potential is at least significant - although with a range from “significant” to “extremely significant”!
DataBank is a data retrieval, analysis, and visualization tool that allows users to create, save, and share custom charts, tables, and maps. We launched the tool two years ago and have been making improvements based on user feedback ever since. Last year we released a multilingual version of the tool, and today we're pleased to announce a new feature that allows users to query country, series, time, and footnote metadata.
What can DataBank do?
- It enables users to easily create custom queries on data drawn from 52 databases
- It lets users create and customize charts, tables, and maps
- It makes it easy to select, save and share data and visualizations
- It's available on both computers and mobile devices
- DataBank and selected data are available in English, Spanish, French, Arabic, and Chinese
- It now allows users to create custom metadata queries
- Watch the tutorial and read the FAQs to learn more about the basics of DataBank
Open Data could be a “Swiss Army Knife” for modern government - a multi-use tool that can be used to increase transparency and accountability, to improve public services, to enhance government efficiency and to stimulate economic growth, business innovation and job creation.
The economic growth opportunity has certainly caught imaginations around the world. The Economist recently likened Open Data’s commercial potential to ‘a new goldmine.’ The McKinsey Global Institute estimated potential economic benefits of at least $3 trillion a year globally, and a recent study for the Omidyar Network by Lateral Economics suggested that, for G20 economies, Open Data could help increase output by $13 trillion cumulatively over the next five years.
Other studies have suggested figures which are lower but still mouth-watering, especially for economies emerging from recession or facing anaemic growth. These are topics we will discuss at a World Bank-sponsored event on July 23, titled “Can Open Data Boost Economic Growth and Prosperity?”
Over the last decade, ICTs have contributed to globalization, shaped economies, transformed society and changed our history. Companies that didn’t exist in 2003 – including Facebook and Twitter – are now essential components of media strategies and contribute to job creation. Broadband drives economic development across the world, and there are more than seven billion mobile cellular subscriptions.
Despite this meteoric change, we’re not quite there yet. While billions of people are already connected to these systems and opportunities, we need much more collaboration to bring about an information society for everyone.
There were more than 7 billion people on earth in 2013. While this is the highest number ever, the population growth rate has been steadily declining, in part due to declining fertility rates. Tomorrow, Friday, July 11, is World Population Day, and in this spirit, I'd like to talk about a key component of population growth: fertility rates.
The wbopendata Stata module has been updated to Version 13. The module can now be installed or updated directly from Stata's Statistical Software Components (SSC) repository.
To install or update your current wbopendata Stata module, please type the below text in the Stata command line:
ssc install wbopendata, replace
- Updated list of indicators with more than 2,000 new indicators, making a total of 9,900 indicators available
- A revised list of country and regional codes
- Five newly added topics: climate change, external debt, gender, Millennium Development Goals, and trade
- A fully redesigned help file
- A revised error reporting structure to facilitate the identification of connection failures, in particular, timeout errors
Here's an example of a query error caused by an invalid indicator:
The recent Open Government Partnership (OGP) regional events in Bali and Dublin have provided a fertile opportunity for participating countries to showcase their performance in advancing open data reforms and for newer members to learn from their peers. The positive energy and participation at these events was a reminder of the strides achieved in recognizing the importance of open data as a precondition for better development outcomes. This was particularly relevant in the field of fiscal openness where an increasing number of countries demonstrated how they are taking actions towards improving transparency in financial matters.
The fiscal openness working group (FOWG) - a partnership between the Global Initiative on Fiscal Transparency (GIFT), the OGP Secretariat and the Governments of Brazil and Philippines - – provided a good opportunity to review the results achieved so far. It produced a background paper that reviewed the status of fiscal commitments. The following highlights stood out in helping us gauge the extent to which fiscal transparency principles are being operationalized in the OGP context:
Millions of soccer fans around the world have their eyes glued to Brazil for the FIFA World Cup games. In light of this, let's take a look at the World Bank's Open Data sets to get a closer look at Brazil, the world's fifth most populous country, and its neighbors.
- Population: 199 million
- Surface area: 8.5 million sq. km
- Terrestrial protected areas: 26.3% of total land
- World's fourth largest cereal/dry grain producer
(dates of the data may vary)
Two previous posts outlined plans to review the World Bank's analytical income classification, here and here. Since we are updating this classification with new data soon (July 1, 2014), we wanted to let users know where this work stands.
Every year, the analytical classification groups all economies into four categories: low income countries (LICs); lower middle income countries (LMICs); upper middle income countries (UMICs); and high income countries (or HICs). This year we will update the classification using 2013 data, but we will not make any change to the methodology.