By Tim Berners-Lee, Wendy Hall, James A Hendler
A Framework for net technology units out a chain of ways to the research and synthesis of the realm broad net, and different web-like details buildings. A complete set of study questions is printed, including a sub-disciplinary breakdown, emphasising the multi-faceted nature of the net, and the multi-disciplinary nature of its research and improvement. those questions and methods jointly set out an schedule for net technological know-how, the technological know-how of decentralised info structures. net technological know-how is needed either on the way to comprehend the net, and to be able to concentration its improvement on key communicational and representational standards. A Framework for net technological know-how surveys relevant engineering concerns, resembling the advance of the Semantic net, net companies and P2P. Analytic methods to find the Web's topology, or its graph-like buildings, are tested. eventually, the net as a know-how is basically socially embedded; accordingly quite a few matters and specifications for internet use and governance also are reviewed. A Framework for internet technological know-how is aimed basically at researchers and builders within the sector of Web-based wisdom administration and data retrieval. it is going to even be a useful reference for college students in desktop technology on the postgraduate point, lecturers and business practitioners.
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Additional resources for A Framework for Web Science
In the ﬁrst place, natural language is a very sparse domain, in that most sentences uttered or written occur once only or very rarely, and the giant scale of the Web provides a fascinating corpus for NLP reasoning. 1% German. Many relatively uncommon languages such as Slovenian or Malay can boast 100m words online, the same size as the widely-used and respected British National Corpus. There are arguments about how representative the Web is as 50 Engineering the Web a corpus, but the notion of what a corpus should represent – should it include speech, writing, background language such as mumbling or talking in one’s sleep, or errors for example?
259]). But this is not an SW requirement. In fact, the SW’s attitude to ontologies is no more than a rationalisation of actual data-sharing practice. Applications can and do interact without achieving or attempting to achieve global consistency and coverage. A system that presents a retailer’s wares to customers will harvest information from suppliers’ databases (themselves likely to use heterogeneous formats) and map it onto the retailer’s preferred data format for re-presentation. Automatic tax return software takes bank data, in the bank’s preferred format, and maps them onto the tax form.
2 Distributed approaches: Pervasive computing, P2P and grids There are many hardware environments which the Web will be expected to penetrate, yet where engineering assumptions that apply 44 Engineering the Web to large-scale, more-or-less ﬁxed dedicated computing machines don’t necessarily apply. Obvious examples include mobile computing, ubiquitous (or pervasive) computing where interoperability becomes an issue, P2P systems and grid computing. Mobile computing makes all sorts of engineering demands; the computing power available isn’t vast and users must be assumed to be constantly on the move with variable bandwidth and access.