A Responsive Framework for Research Portals Data using Semantic Web Technology

TL;DR

This paper presents a framework that uses Semantic Web technologies to organize and access research data from portals like Microsoft Academic and IEEE Xplore, improving data retrieval efficiency.

Contribution

It introduces a novel framework for semantic organization of research portal data, specifically targeting Microsoft Academic and IEEE Xplore, to streamline data collection.

Findings

Enhanced accessibility and interpretability of research data

Reduced time and effort in data collection for researchers

Promotes use of Semantic Web in academic data management

Abstract

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.