Semantic document architecture for desktop data integration and management
Thèse de doctorat : Università della Svizzera italiana, 2010 ; 2010INFO008.
Over the last decade, personal desktops have faced the problem of information overload due to increasing computational power, easy access to the Web and cheap data storage. Moreover, an increasing number of diverse end-user desktop applications have led to the problem of information fragmentation. Each desktop application has its own data, unaware of related and relevant data in other... MoreAdd to personal list
- Over the last decade, personal desktops have faced the problem of information overload due to increasing computational power, easy access to the Web and cheap data storage. Moreover, an increasing number of diverse end-user desktop applications have led to the problem of information fragmentation. Each desktop application has its own data, unaware of related and relevant data in other applications. In other words, personal desktops face a lack of interoperability of data managed by different applications. Recent years have also seen the rapid growth of shared data in online social network communities. Desktop users have been publishing extensively data from their personal desktops to different social-networking sites. In the current data- publishing scenario, desktop data that is published to a social network becomes completely disconnected from desktops they originate. Moreover, there is no interoperability between the same desktop data published to different social networks. A core idea of a Social Semantic Desktop vision is to enable semantic integration and data interoperability on the personal desktop by applying Semantic Web technologies, and to connect data from personal desktops into a unified information space of social network communities. This thesis introduces a new form of documents, called Semantic Documents, which attempts to bring desktop documents closer to this vision and provides a software architecture, namely Semantic Document Architecture (SDArch) that supports semantic documents. Semantic documents enable unique identification, semantic annotation, and semantic linking of fine-grained units of documents’ data. Semantic links can be established between the semantically related document data units, whether they are stored on the same personal desktop or shared within social networks. Therefore, semantic documents integrate data of desktop documents into a unified desktop information space as well as fill the gap between the desktop information space and the information space of the social network communities. New processes such as the semantic document search and navigation, which are enabled by such integrated desktop information space, improve the effectiveness and efficiency of desktop users in carrying out their daily tasks. The thesis’s main contributions are the development of the Semantic Document Model (SDM) that describes semantic documents and the design of SDArch that provides solutions for the semantic document repository, services that support semantic documents related processes, and tools that enable desktop users to interact with semantic documents. Additionally, in order to validate the thesis I implemented the SDArch prototype, which is a fully-functional software providing the implementation of all the intended SDArch functionalities. The thesis is validated by two evaluation studies: i) the experimental evaluation of the information retrieval in integrated collections of semantic documents, and ii) the usability evaluation of the user effectiveness, efficiency, and satisfaction in using the SDArch services and tools. The results of these two evaluation studies proved that semantic documents have potential to semantically integrate and improve interoperability of desktop data, thus improving the effectiveness and efficiency of desktop users while carrying out their daily tasks.