  As the amount of data on the World Wide Web continues to grow exponentially,
access to semantically structured information remains limited. The Semantic Web
has emerged as a solution to enhance the machine-readability of data, making it
significantly more accessible and interpretable. Various techniques, such as
web scraping and mapping, have been employed by different websites to provide
semantic access. Web scraping involves the extraction of valuable information
from diverse data sources, such as the World Wide Web, utilizing powerful
string manipulation operations.In the research field, researchers face the
challenge of collecting relevant data from multiple sources, which requires
substantial time and effort. This research aims to address this issue by
designing a framework for the semantic organization of research portal data.
The framework focuses on the extraction of information from two specific
research portals, namely Microsoft Academic and IEEE Xplore. Its primary
objective is to gather diverse research-related data from these targeted
sources.By implementing this framework, researchers can streamline the process
of collecting valuable information for their work, saving time and effort. The
semantic organization of research portal data offers enhanced accessibility and
interpretability, facilitating more effective and efficient knowledge
discovery. This research contributes to the advancement of research data
management and promotes the utilization of semantic web technologies in the
academic community.
