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the areas of ontology merging and mapping offers the prospect of seamless access to distributed information As long ago as 1995 a workshop held under the auspices of the US Government s Information Infrastructure Technology and Applications Working Group identi ed ve key research areas for digital libraries (Lynch and Garcia-Molina, 1995): 1 Interoperability: At one level this is about the interoperability of software and systems At a deeper level, however, it is about semantic interoperability through the mapping of ontologies Indeed deep semantic interoperability has been identi ed as the Grand Challenge of Digital Libraries (Chen 1999) 2 Description of objects and repositories: This is the need to establish common schema to enable distributed search and retrieval from disparate sources.

useful for electronic purposes synchronization uses the term vCard for a standard way of storing contact information An address card is represented by a CContactCard object but requires very little additional functionality most of its behavior is contained in the CContactItem class A CContactCard has a unique identi er and a set of elds that contain the actual card data It can belong to zero or more groups of cards A CContactCard can be found either directly by means of its identi er or by lters or searches The address card that belongs to the mobile phone owner is a standard card in most ways It is identi ed separately because it can be used to identify the phone It can be beamed to another phone and it could be used for an information screen Therefore, the CContactOwnCard class is derived from CContactCard rather than directly from CContactItem.

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Effectively, how can we create an ontology for searching and browsing into which we can map individual library ontologies Going further, how can we enable individual users to search and browse within the context of their own personal ontologies 3 The collection and management of nontextual information: This includes issues relating to the management, collection and presentation of digital content across multiple generations of hardware and software technologies Moreover, libraries are now much more than collections of words, but are increasingly rich in audiovisual material, and this raises new research challenges 4 User interfaces: We need better ways to navigate large information collections One approach is through the use of visualisation techniques The use of ontologies not only helps navigation but also provides a basis for information display 5 Economic, Social and Legal Issues: These include digital rights management and the social context of digital documents .

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Because the set of elds that an address card owns can be relatively complex and can be extended, it is necessary to have some method of setting the elds that a newly created card is given This is done using templates A CContactCardTemplate object contains details of elds and can be used when creating a new CContactCard Going beyond address cards, the CContactGroup class represents a group of address cards (actually, a group can be a member of other groups as well) A group has a label and a list of the CContactItems that it contains Note that a group does not own the CContactItems that it contains a CContactItem can be a member of more than one group It may help to regard a CContactGroup as a club a person can be a member of any number of clubs from zero upwards.

Axioms 1 and 2 are fairly obvious; the probability assigned to the entire sample space must be 1 since by de nition of the sample space some point in the sample space must occur and the probability of an event must be between 0 and 1 Now if an event A occurs with probability P(A) and an event B occurs with probability P(B) and if the events cannot occur together, then the relative frequency with which one or the other occurs is P(A) + P(B) For example, if a prospective student decides to attend University A with probability 2/5 and to attend University B with probability 1/5, she will attend one or the other (but not both) with probability 2/5 + 1/5 = 3/5 This explains Axiom 3 It is also very useful to consider an event, say A, as being composed of distinct points, say ai ,with probabilities p(ai ) By Axiom 3 we can add these individual probabilities to compute P(A) so

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