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By 2020, micro p rocessors will likely be as cheap and plentiful as scrap paper, s c a t t e red by the millions into the environment, allowing us to place intelligent systems eve ry w h e re. This will change eve rything around us, including the nature of commerce, the wealth of nations, and the way we communicate, work, play, and live. This will give us smart homes, cars, T V s , j e we l l e ry, and money. We will speak to our appliances, and they will speak back. Scientists also expect the In t e rnet will wire up the entire planet and evo l ve into a membrane consisting of millions of computer networks, creating an "intelligent planet." The In t e rnet will eventually become a "Magic Mi r ro r" that appears in fairy tales, able to speak with the wisdom of the human ra c e. Michio Kaku, Visions: How Science Will Re vo l u t i o n i ze the Twe n t y-Fi r s t C e n t u ry, 1998 If the semantic web needed a symbol, a good one to use would be a Na va h o d ream-catcher: a small we b, lovingly hand-crafted, [easy] to look at, and ru m o red to catch dreams; but really more of a symbol than a re a l i t y.

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Recent work on applying semantic technologies to learning has concentrated on providing novel means of accessing and making use of learning objects. However, this is unnecessarily limiting: semantic technologies will make it possible to develop a range of educational Semantic Web services, such as interpretation, structure-visualization, support for argumentation, novel forms of content customization, novel mechanisms for aggregating learning material, citation services and so on. In this paper, we outline an initial framework that extends the use of semantic technologies as a means of providing learning services that are owned and created by learning communities.

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