Group items tagged

"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

Contributors consider the concept of the commons historically and offer an analytical framework for understanding knowledge as a shared social-ecological system. They look at ways to guard against enclosure of the knowledge commons, considering, among other topics, the role of research libraries, the advantages of making scholarly material available outside the academy, and the problem of disappearing Web pages. They discuss the role of intellectual property in a new knowledge commons, the open access movement (including possible funding models for scholarly publications), the development of associational commons, the application of a free/open source framework to scientific knowledge, and the effect on scholarly communication of collaborative communities within academia, and offer a case study of EconPort, an open access, open source digital library for students and researchers in microeconomics. The essays clarify critical issues that arise within these new types of commons-and offer guideposts for future theory and practice.

The OSI-MMX controversy. "So, in my view, the OSI should not give in to this blackmail, but should stand firm on the fundamental principle that software patents are an unmitigated harm for free software. It should reject the current proposed licence, and insist that if the MPEG Working Group wishes to benefit from open source, it should play by open source's rules."

"Open Government Data Principles Government data shall be considered open if it is made public in a way that complies with the principles below: 1. Complete All public data is made available. Public data is data that is not subject to valid privacy, security or privilege limitations. 2. Primary Data is as collected at the source, with the highest possible level of granularity, not in aggregate or modified forms. 3. Timely Data is made available as quickly as necessary to preserve the value of the data. 4. Accessible Data is available to the widest range of users for the widest range of purposes. 5. Machine processable Data is reasonably structured to allow automated processing. 6. Non-discriminatory Data is available to anyone, with no requirement of registration. 7. Non-proprietary Data is available in a format over which no entity has exclusive control. 8. License-free Data is not subject to any copyright, patent, trademark or trade secret regulation. Reasonable privacy, security and privilege restrictions may be allowed."

An article that looks at the open source hardware initiative.

Using open source software was about "better and more effective government". He criticised government IT procurement for lacking "open standards" and making it difficult for small companies to get the contracts. "All too often a government IT system is incompatible with other types of software, which stifles competition and hampers innovation. "Looking at the litany of IT projects that have collapsed or spiralled over budget, it's clear too that this has meant billions of pounds wasted and public service reform being hampered," Mr Osborne said. "The government's approach needs to be overhauled."

National Income 1.0 Gross Domestic Product 1.1 State Domestic Product 1.2 Input- Output Table Agriculture * Land utilisation statistics * Area under principal crops * Production of principal crops * Average yield of principal crops * Availability of food grains * Net and gross area irrigated Transport * Railways- General statistics * Total road length by surface, Number of registered motor vehicles * Civil Aviation- Domestic services-International services * Shipping Industry * Production of selected items of major manufacturing industries * Index number of industrial production (Base:1993-94=100) * Annual survey of industries: Employment and value added -Statewise :Factory sector - 2003-04 & 2004-05 * Performance of Small Scale Industries Sector Energy * Primary source of energy (production) * Electricity: Generated and sold * Rural electrification in India Communication * Posts Telegraphs and Telephones Employment * Employment in public and private sector * Employment in Railways, Insurance * Factory employment * employment in banking,plantation Poverty & Employment Tourism * Number of foreign tourists to India by country of nationality * Prices * Index number of wholesale prices (By major groups and sub-groups) (Base: 1993-94=100) * Index number of consumer prices - Industrial workers (Base: 1982=100) * Index number of consumer prices - Agricultural labourers (Base: 1986-87=100) * Index number of consumer prices - Urban non-manual employees (Base: 1984-85=100) Social Statistics Balance of Payments * Overall balance of payments - Current account. * Overall balance of payments - Capital account. * Financing of payment deficits by plan periods * Foreign exchange reserves * External assistance - authorization and utilization classified by source Public Finance * Overall budgetary posit

At the Governor's request, Secretary Thomas will work with State Superintendent of Public Instruction Jack O'Connell and State Board of Education President Ted Mitchell to develop a state approved list of standards-aligned, open-source digital textbooks for high school math and science. This list will be compiled after content developers across the country are asked to and have submitted digital material for review.

"The common Western narrative of China is of a country whose businesses unfairly compete by stealing intellectual property from others and making money off of copycat technology. While undoubtedly a large amount of IP theft does happen in China, its hard to believe that anyone can look at China and not see innovation everywhere. I've noticed that this question of innovation in China comes up often among Western observers of China. Why? Do we feel that the playing field is unfair? Are we in the U.S. desperately looking for signs of an enduring competitive advantage even as we've shipped our entire manufacturing base overseas? I'm not sure, but the topic sure comes up a lot. Yes, China can innovate, but what kind of innovation? Jacob Hsu (Symbio) remarked that in Silicon Valley, investors and entrepreneurs are looking for "business model" innovation, which I interpreted to mean a new product that creates new markets. He characterized Chinese innovation as mostly incremental "technology" innovation in the past, but that increasing we were seeing highly innovative companies emerge, such as Tencent. He also highlighted the phenomenon of "shanzhai" as an example of innovation on a much smaller scale. The "shanzhai" consumer electronics economy in China is rapidly creating next generation connected devices out of laptop and mobile phone components, and that in most cases the minimum scale required to produce these units can be as small as a few hundred units to make money. Conventional wisdom equates intellectual property protection with innovation. But the "shanzhai" phenomenon challenges this idea. Could the lack of intellectual property protection create opportunities to remix, modify and mashup existing technology that creates an "innovation capability" for China's entrepreneurs even as the lack of IP protection prevents them from fully capitalizing on their successes (because the next guy will just rip them off)? In this