Improving Research Information Retrieval with Semantic Web Technologies

Title: Improving Research Information Retrieval with Semantic Web Technologies

Abstract: This research aimed to enhance research information retrieval systems using Semantic Web technologies. The study developed an ontology for research information systems and proposed an architecture for collecting and accessing research data. The results showed that Semantic Web technologies could improve information retrieval by integrating data from various sources, providing complete and actual information, and facilitating data access for researchers, industry, and policy-makers.

Main Research Question: How can Semantic Web technologies be used to improve research information retrieval systems?

Methodology: The study utilized the DAML (DARPA Agent Markup Language) and RDF (Resource Description Framework) technologies, which are part of the Semantic Web. It developed an ontology for research information systems and designed an architecture for collecting and providing access to research data. The system was tested using data from Austrian universities.

Results: The study found that Semantic Web technologies could help integrate data from various sources, making it easier for users to access complete and actual information. The use of ontologies allowed for better understanding and organization of research data, while the architecture enabled efficient data retrieval and integration.

Implications: The research suggests that Semantic Web technologies can significantly improve research information retrieval systems. By integrating data from diverse sources and providing better access to research information, these technologies can benefit researchers, industry, and policy-makers alike. The study also highlights the importance of developing flexible and easy-to-implement systems for data integration and information retrieval.

Link to Article: https://arxiv.org/abs/0110026v1 Authors: arXiv ID: 0110026v1