If a child is born today in a country where the life expectancy is 75, they can expect to live until they are 75… right?
The statistic “Life expectancy at birth” actually refers to the average number of years a newborn is expected to live if mortality patterns at the time of its birth remain constant in the future. In other words, it’s looking at the number of people of different ages dying that year, and provides a snapshot of these overall “mortality characteristics” that year for the population.
हमारी दुनिया आँकड़ों की बढ़ती हुई मात्रा से भरी हुई है, परन्तु संभावित दर्शकों के लिए ये आँकड़े कम उपयोगी होते हैं जिसका सबसे स्वाभाभिक कारण है - आँकड़े उनकी भाषा ही नहीं बोलते हैं।
Although I now live in Washington DC, I’m from Cambridge in England. I still like to keep track of my Member of Parliament (MP) back home, Julian Huppert, using a site first developed in 2004 by mySociety called TheyWorkForYou.
It presents an aggregation of data on MPs from sources including official transcripts of parliamentary discussions (Hansard), election results, the Register of Interests and Wikipedia entries. In short, it’s a “digital dossier” on all of the country’s parliamentarians.
But take another look at Jullian’s page and the “Numerology” section halfway down. Isn’t it reassuring to see that he: “Has used three-word alliterative phrases (e.g. "she sells seashells") 244 times in debates — average amongst MPs.”
Our world is awash with increasing amounts of data, but potential audiences for this data remain under-served for the most obvious of reasons - the data just doesn’t speak their language.
This has been true for the data on the World Bank Group Finances website which has only ‘spoken’ English since it was launched. Yes, we should have done this earlier but the website, and its associated open datasets, are now available in 5 new additional languages - Chinese, French, Hindi, Russian, and Spanish . The mobile app has been available for some time in 9 languages (Arabic, Chinese, English, French, Hindi, Indonesian Bahasa, Portuguese, Russian, and Spanish) and the new release of the website is in line with the program’s quest to include new audiences and communities in the use and dissemination of open financial data.
As the “Data Revolution” takes shape, Multilateral Development Banks, the UN, and IMF have already begun to improve their collaboration on development data.
This process was launched on April 19, 2013, when Heads of these institutions signed a Memorandum of Understanding (MOU) that sets out the basis for enhanced collaboration in statistical activities. In short, the MOU is part of the global response to the evidence focus of the post-2015 agenda, and the eagerness for policy makers to accelerate the quantity, quality, availability, and usability of data for development.
A revolution needs revolutionaries (and here are a couple of genuine data pioneers). But how can diverse groups around the world come together to help make development data better? The panel proposes a new “Global Partnership on Development Data”; this post proposes a first idea of how this might work and how it might differ from past efforts. I’d like to know what you think.
The open data community is chock-full of do-gooders.
There are "open" data-driven applications that track government legislation in the US, tools that help calculate taxi fares in Bogota, Colombia, applications that track how tax payer funds are spent in the UK, the state of school sanitation in Nepal, and many more.
It's clear that innovators are out there and full of terrific ideas about how to help their fellow citizens by harnessing public data. The question is, how can more of these projects follow examples like GovTrack and transition from hobby to successful, sustainable business models? And while there may be technical talent out there, what about entrepreneurial skills? How many data rockstars out there also have the "courage to create a business"?
The World's CO2 emissions grew 4.9% in 2010
That's the 3rd largest annual increase since 1990 (early estimates of 2011 and 2012 emissions show further global increases since 2010, but not quite as large). Nationally, China, the United States, India, Russia and Japan continue to be the top 5 emitters. It's also notable that in 2010 South Korea surpassed Canada in 8th place, and South Africa fell out of the top 10 with an emissions drop of almost 3 percent.