How do you take the same data that everybody has access to and convert it into a billion dollar business? When do you look at all the data in the world and say you want more (and that you are going to collect it like no one has done before)? How do you stop worrying about open data, and begin solving development challenges instead? Who is doing what with open data and how and why?
The latest data from the Inter-Parliamentary Union show that Rwanda tops the list as the country with the highest proportion of women in parliament, with nearly 64 percent of seats held by women in 2013. Globally, women account for an average of about 20 percent of parliamentary seats, up from 15 percent a decade ago.
The top ten countries are a mix of high and middle income economies, some with legally mandated gender quotas and some without. Rwanda, a low income country, is followed by Andorra at a flat 50 percent and Cuba at 49 percent. Sweden, with 44 percent of parliamentary seats held by women, is the country that achieved the highest rate without any gender quota.
Data tells stories and the people at the World Bank Group who fight fraud and corruption are keen to listen.
What do these changing costs tell us about the integrity of the project?
Could it be that the cost of supplies is evolving in a suspicious way for a particular project?
Also available in Bahasa
It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts. – Sherlock Holmes.
It's a game changer for those working on Indonesia's sub-national development issues. Comprehensive data at the sub-national level is now available to the public through INDO-DAPOER (Indonesia Data for Policy and Economics Research) at data.worldbank.org. DAPOER, which means ‘kitchen’ in Indonesian, is intended to be a ‘place’ where various data are blended, like spices, and cooked to produce analytical works, research papers, and policy notes.
INDO-DAPOER is the first World Bank sub-national database consisting of both province and district level data to be publicly accessible from anywhere in the world. The database provides access to around 200 indicators from almost 500 districts and 34 provinces in Indonesia, which in general go back to the early 1990s and even 1980s for some. The indicators are grouped into four main categories: fiscal, economic, social demographic, and infrastructure. Indicators range from sub-national government revenue and expenditure, sub-national GDP, to specific education, health, and infrastructure indicators such as net enrollment rate for junior secondary, immunization rate, and household access to safe sanitation.
Can open data lead to reduced energy consumption (and therefore slow down climate change)? Can open data help improve maternal health services (and thus improve facets of public delivery of services)? Can open data help farmers and crop insurers make better crop predictions (and thus lead to smarter investment decisions in agriculture)? Can open data empower citizens to fight back against police corruption (and thus help promote the rule of law)?
क्या ओपन डेटा (खुला/सर्वसुलभ डेटा) की वजह से ऊर्जा खपत में कमी आ सकती है (और इसलिए जलवायु परिवर्तन धीमा हो सकता है)? क्या ओपन डेटा से मातृत्व स्वास्थ्य सेवाएं बेहतर हो सकती हैं (और इस तरह सेवाओं के सार्वजनिक वितरण संबंधी पहलुओं को बेहतर किया जा सकता है)? क्या ओपन डेटा से किसानों और फसल बीमाकर्ताओं को फसल संबंधी पूर्वानुमान लगाने में मदद मिल सकती है (और इस तरह कृषि में निवेश के अधिक समझदारी वाले निर्णय लिये जा सकते हैं)? क्या पुलिस भ्रष्टाचार से लड़ने में ओपन डेटा नागरिकों को सशक्त कर सकता है (और इस तरह कानून के शासन को प्रोत्साहित करता है)?
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.