Developing Information Dissemination Platform Combined with Semantic Web-based Inference Services

Hanmin Jung, KISTI, Korea


The importance of systematized information dissemination based on knowledge management systems or contents management systems grows more and more in the environment that information is intemperately created in great quantities. However, the studies on knowledgization and information verification, in particular, by Semantic Web-related communities, were independently performed regardless of information dissemination workflow. The separation between the two research fields brought on Semantic Web-based services without consideration on dynamic information life cycle including creation, storing, management, search, and dissemination.

There are a few successful Semantic Web applications such as CAS (CS AKTive Space) of AKT (Advanced Knowledge Technologies) project and SEAL (Semantic portAL). Even in Korea, no case is found to manage real data yet. Previous Semantic Web-based services were designed and implemented to provide static knowledge service, that is, they have no real-time knowledgization process to reflect up-to-date information. On the other hand, our platform adds DB-to-OWL Conversion process to instantly update new information. The results of the process, i.e. individuals, are also asserted into main ontology for keeping knowledge consistency. It is absolutely insufficient for Semantic Web-based services on information dissemination platform. Most of the previous studies focus on the type and the specification of information.
Thus we focus on the verification and the tracing of information on information dissemination platform, and further Semantic Web-based services. Services on our platform include information dissemination service to support reliable information exchange among researchers and knowledge service to provide unrevealed information.

Information dissemination service is based on client-server model. To organize and to provide collaboration, a central knowledge server should be constructed. Each verified client requests and downloads his/her necessary information to it. After creating or modifying, information would be uploaded to the server. A successive workflow of the above events establishes voluntary information dissemination service. Knowledgization is defined as the process to systematize national R&D reference information using ontology. Inference uses RDF triples which are the results of knowledgization. It acquires unrevealed information using facts, rules, and even post-processing to manipulate retrieved information.

Our ontology for national R&D reference information consists of 7 top classes; Event, Group, Intellectual Property, Person, Project, Publication, and Research Topic. The whole number of classes is 74. We also defined 75 properties and several restrictions including someValuesFrom, allValuesFrom, and minCardinality. As the reference information, about 2,300 documents with metadata were collected from KISTI (Korea Institute of Science and Technology Information) products. Jena finally generated 37,656 RDF triples from them. Thesaurus for query expansion includes about 15,000 concepts which were manually selected out of about 50,000 terms extracted by means of term life cycle methodology. It is possible to say that the platform showed a new paradigm to disseminate information owing to ontology-based inference on Semantic Web. As a future work, we have a plan to provide knowledge-based fusion service by mutual interlocking between information dissemination service and knowledge service.


Keywords: Semantic Web, Information Dissemination, Ontology