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"Where GoogleSharing Comes In GoogleSharing is a system that mixes the requests of many different users together, such that Google is not capable of telling what is coming from whom. GoogleSharing aims to do a few very specific things: Provide a system that will prevent Google from collecting information about you from services which don't require a login. Make this system completely transparent to the user. No special websites, no change to your work flow. Leave your non-Google traffic completely untouched, unredirected, and unaffected. The GoogleSharing system consists of a custom proxy and a Firefox Addon. The proxy works by generating a pool of GoogleSharing "identities," each of which contains a cookie issued by Google and an arbitrary User-Agent for one of several popular browsers. The Firefox Addon watches for requests to Google services from your browser, and when enabled will transparently redirect all of them (except for things like Gmail) to a GoogleSharing proxy. There your request is stripped of all identifying information and replaced with the information from a GoogleSharing identity. This "GoogleShared" request is then forwarded on to Google, and the response is proxied back to you. Your next request will get a different identity, and the one you were using before will be assigned to someone else. By "sharing" these identities, all of our traffic gets mixed together and is very difficult to analyze. The result is that you can transparently use Google search, images, maps, products, news, etc... without Google being able to track you by IP address, Cookie, or any other identifying HTTP headers. And only your Google traffic is redirected. Everything else from your browser goes directly to its destination. "

The emphasis in MGNREGA is now on ensuring public accountability, strengthening transparency and encouraging activities that tap the productive potential of works undertaken so that it becomes a platform for sustainable development. In order to enforce transparency at the grass root level, the Ministry Of Rural Development intends to use ICT devices, especially Biometrics and integration with UIADAI to introduce biometric attendance on site and to improve the overall delivery system in the implementation of MGNREGA by capturing all the processes right from registration, demand of work, issue of dated receipt, allocation of work, attendance at worksite with GPS coordinates, measurement of work and wage payments.

Zainab Bawa: "It is presumed that providing such information will encourage people to engage with the state and participate in monitoring its activities. My aim in this post is to dissect this logic somewhat further and to highlight some of the political dynamics which complicate any simple understandings of transparency and information access. I will conclude this post by making some tentative remarks on the possible ways in which information access can be configured in order to serve certain local needs."

The strategy contains more than thirty concrete recommendations for improvement, falling into six main categories. First, we will lead by example. Specifically, we will work to ensure that we do not mistakenly purchase or use illegal products. Second, the strategy underscores that this Administration supports transparency. That includes transparency in our development of enforcement policy, information sharing, and reporting of law enforcement activities at home and abroad. Third, we will improve coordination and thereby increase efficiency and effectiveness of law enforcement efforts at the Federal, state and local level, of personnel stationed overseas and of our international training efforts. Fourth, we will work with our trading partners and within international organizations to better enforce American intellectual property rights in the global economy. In that regard, we will initiate a comprehensive review of current efforts in support of U.S. businesses that have difficulty enforcing their intellectual property rights in overseas markets, with a particular focus on China. Fifth, we must secure our supply chain. To achieve this most important goal, we will take a close look at the unique problems posed by foreign-based websites and other entities that provide access to counterfeit or pirated products, and develop a coordinated and comprehensive plan to address them. We will make sure our law enforcement has the authority it needs to secure the supply chain and also encourage industry to work collaboratively to address unlawful activity on the internet, such as illegal downloading and illegal internet pharmacies. Sixth, and finally, we will make sure we spend your money wisely, a process we have already begun. To do that, we have, and will continue to collect and track the amount of money we spend on intellectual property enforcement per year. We will use this information to map out the most effective way to fight this theft.

As the impact of digital advertising on consumer privacy comes under scrutiny, AT&T is taking a stance in support of stricter standards. In its testimony Thursday at a House subcommittee hearing on the issue, the telecommunications heavyweight is expected to advocate more transparency and consumer control in the fast-growing field of targeted ads.

"Open source software developers have a powerful set of tools to make distributed authoring of software possible: diff to identify what's changed, patch to apply those changes elsewhere, version control to track changes over time and show provenance. Patch management would be just as important in a collaborative open data project, where users and other researchers might be submitting new or revised data. What would git for data look like? Heck, what would a local branch look like? I have a new attribute, you have a different projection, she has new rows, how does this all tie back together? (I eagerly await claims that RDF will solve this problem and all others) That's just development. The interface between developers and users is the release. State of the art for a lot of government data is the equivalent of source.tar.gz. No version numbers, much the ability to download older versions of the datasets or separate stable and development branches. Why would we want to download the historic version of a dataset? Because a paper used it and we want to test the analysis software that the paper used to ensure we get the same answer. Or because we want to see what our analysis technique would have shown with the knowledge that was available back then. Or simply to be able to track defects. The users of data will have to adapt to the idea of versions, like the users of software have. The maintainers of the dataset might release five different versions of it while you're writing your analysis code, so it can't be a painful process to incorporate the revised data into your project. With software we have shared libraries and dynamic libraries, supported by autotools and such packages. Our code has interfaces and a branch that promises backwards compatibility. What would that look like for data? And what is the data version of the dependency hell that software developers know all-too-well (M 1.5 depends on N 1.7 and P 2.0, but P 2.0 requires N 2.0, and upgrading N to 2.0 br

Expenditure and procurement information.

The World Bank announced this week (April 2010) a new open data initiative, which provides free and open access to the Bank's health and development data, including 2,000 social, economic, financial, institutional, and environmental indicators. The World Development Indicators, the Bank's most popular statistical resource, consist of over 900 indicators for 200 countries alone, including many that go back to 1960. The Bank has also opened up access to the Global Development Finance, Africa Development Indicators, Global Economic Monitor, and indicators from the Doing Business Report.

"On 4th June 2010 the UK government released A whole load of useful data about much the governemt has been spending on various things we parse this data for you " This website provides it in easily parseable csv format.