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.
The power of open data to bring together people from different streams of life for civic purposes was on full display around the world on February 22-23, 2014. Washington, D.C. was home to one of the 194 global International Open Data Day events that dotted cities around the world. Data was scraped. Visualizations were made. Code was written. Interfaces were designed. Prototypes were built. Initiatives were born (Here’s looking at you, Code for Nepal!). New friends were made. And a tooth was chipped.
photo credit: @anjelikadeo
Despite the unseasonably warm weather in Washington, D.C., more than 350 civic hackers, development specialists, coders, designers, and enthusiasts participated in two days of Open Data Day hacking and tutorials at the World Bank. Based on an informal poll (raise your hand, please?!) of all attendees at the beginning of the event, nearly two-thirds of the audience had never attended an Open Data Day event before. This was an unexpected but welcome surprise and bodes well for the continued growth of the open data community in Washington, DC.
This post originally appeared on the FeedBack Labs blog.
Feedback is always present. Even silence is not the absence of feedback, but a quiet subtext open for interpretation. In both online and offline communities, the most difficult part is not generating feedback or even collecting it. People typically care about what is happening around them and are often willing to share their sentiments and reflections- sometimes even unable to hold back expression. The advent of writing perhaps marks an innate human desire to share information and to be heard without speaking; “true” silence may actually be quite rare, more a condition of looking and listening in the wrong places or employing a less holistic approach. The graffiti that marks the architecture of repressive regimes past and present is in itself a type of feedback, representing citizen engagement with institutions that refused to officially afford that right or offer practical channels to its citizens. As such, the key challenges that exist with feedback loops are whether or not we are listening, engaging, and actively responding by catalyzing appropriate change.
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.
The World Bank has been collecting statistics on the debt of its borrowing countries since 1951, through the Debtor Reporting System. Published for many years as World Debt Tables (see, for example, the 1982 edition here) and then as Global Development Finance (initially as Volume 2), the 2013 dataset - which contains data for 2011 - was published in a renamed publication as International Debt Statistics, with expanded coverage of Quarterly External Debt Statistics and Public Sector Debt.
Last year we reviewed our dissemination strategy for World Development Indicators (WDI), and made some improvements to improve the quality and accessibility of the statistical indicators, tables and analyses. This year we’ve looked at debt statistics, and are planning some changes here as well; while the 2014 dataset - which contains data for 2012 - has been released in mid-December as usual, we’ll be releasing the redesigned data products in mid-February.
The world economy is projected to strengthen this year, with growth in high-income economies appearing to be finally turning the corner five years after the global financial crisis, according to the World Bank’s newly-released Global Economic Prospects (GEP) report.
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)?