APPLYING SEMANTIC TECHNOLOGY TO A DIGITAL LIBRARY in VS .NET

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account when faced with trade-offs in designing systems, and to be further tested by users reaction to real semantic digital library systems.
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11.5. IMPLEMENTING SEMANTIC TECHNOLOGY IN A DIGITAL LIBRARY 11.5.1. Ontology Engineering
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A well-designed ontology is essential for a successful semantic application. Within SEKT we are adopting a layered approach. In the lower layers we have a general ontology, which we call Proton (PROTo Ontology, http://proton.semanticweb.org). The classes in this ontology are a mixture of very general, for example Person, Role, Topic, TimeInterval and classes which are more speci c to the world of business, for example Company, PublicCompany, MediaCompany. See 7 for more detail. Above this we have the PROTON Knowledge Management ontology, which contains classes relating to knowledge management. Examples are UserPro le and Device. Finally, each of our three case studies has its own domain-speci c ontology. In the case of the digital library, this will contain classes relating to the speci cs of the library, for example to the particular information sources available. A strength of an approach based on the use of an ontology language such as OWL, is the ability to accommodate distributed ontology creation activities, for example through de ning equivalences. Nonetheless, where possible the creation of duplicate ontological classes should be avoided and where appropriate we make use of existing well-established ontologies, for example Dublin Core.8 Mention has been made of the use of a topic hierarchy. Within PROTON there is a class, Topic . Each individual topic is an instance of this class. However, frequently a topic will be a sub-topic of another topic, for example in the sense that a document about the former should also be regarded as being about the latter. Since topics are instances, not classes, we cannot use the inbuilt subclass property, but must de ne a new property subTopic. Such a relationship must be de ned to be transitive, in the sense that if A is a sub-topic of B and B is a sub-topic of C, then A is also a sub-topic of C. This approach, based on de ning topics as instances and using a subTopic property rather than de ning topics as classes and using the sub-class relation, is chosen to avoid problems in computational tractability. In particular, this enables us to stay within OWL DL. It follows
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IMPLEMENTING SEMANTIC TECHNOLOGY IN A DIGITAL LIBRARY
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approach 3 in Noy (2005). Again, for a more detailed discussion, see 7.
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11.5.2. BT Digital Library End-user Applications
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The following end user applications are available: (i) (ii) (iii) (iv) a semantic search and browse application, a knowledge sharing application, a personal search agent, semantically enabled information spaces.
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All applications were built upon the core technologies of ontology creation; named entity identi cation and annotation; ontology maintenance and ontology mediation. The semantic search and browse application combines free-text search with a capability to query over the ontology and knowledgebase as described in more detail in 8. The search and browse application augments the more traditional practice of presenting the results of a query as a ranked list of documents with an approach where knowledge contained within documents is presented in a more meaningful way to the user. Named entities, for example company names, are identi ed and relevant supplementary information is presented to the user. In addition, user-speci c, interest-based pro les are constructed in accordance with a user s interaction with the digital library and other WWW and intranet information sources, giving an element of context to the user s search. The semantic knowledge sharing application enables users to annotate digital library documents, WWW or Intranet pages with topics selected (semi-automatically) from the digital library topic ontology, to share that information with colleagues, and to recall annotated pages at a later date more easily. Our user can also add a comment, for subsequent viewing by his colleagues. The essence of our approach is that sharing is not achieved by pushing information to colleagues, for example via email. Instead, web-pages marked by a user as being of particular interest or value, are presented prominently when they occur amongst the search results of that user s colleague, or when he or she comes across them in browsing. The incentive to share arises from the fact that the sharing mechanism is exactly that of bookmarking, that is in bookmarking the page for himself, the user is sharing it with colleagues. The personalised semantic search agent collects relevant content from the digital library and WWW on behalf of a user, and gives improved relevance and timeliness of the delivery of information. Named entities within the search agent s results are highlighted. The approach builds on that of KIM, see 7.
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