The amount of information on the Web is enormous and growing exponentially. Indeed, it is a major challenge to measure the amount of information contained in the Web. It is even harder to assess how much of this information is useful or original. In addition, the information on the Web comes in a huge range of formats from a vast number of disparate sources. All of these aspects raise a crucial research topic: how we are to browse, explore and query the Web at this scale? Once again, this theme requires the inter-disciplinary approach embodied in Web Science. From a computer science perspective, we need to know how inference can be supported at the Web scale; for example, how can context be represented and supported? What do psychology and linguistics tell us about the design of interfaces for querying complex data? How can the data sources within the Web be exploited to help us to develop understanding of the sociological aspects of the Web? Understanding the possibilities for inference online is an important skill for those moving into scientific research and development.
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