Enabling Web-scale data integration in biomedicine through Linked Open Data

Area of Science:

• Biomedical Informatics
• Semantic Web Technologies
• Linked Data Principles

Background:

• Biomedical data is fragmented across diverse, heterogeneous sources with varying formats and notations.
• Researchers face significant challenges in querying, integrating, and analyzing data from multiple sources.
• Semantic Web and Linked Data principles offer potential for Web-scale semantic processing and data integration.

Purpose of the Study:

• To explore the opportunities of Life Sciences Linked Open Data (LSLOD) for biomedical data integration.
• To examine LSLOD applications in pharmacology, cancer research, and infectious diseases.
• To identify challenges and propose solutions for LSLOD adoption in biomedical research.

Main Methods:

• Perspective paper discussing the application of LSLOD principles.
• Analysis of opportunities in specific biomedical domains.
• Identification of challenges and technical solutions for LSLOD utilization.

Main Results:

• LSLOD presents opportunities for integrating biomedical data in pharmacology, cancer, and infectious diseases.
• Several challenges hinder the widespread use and consumption of LSLOD.
• Technical solutions and insights are proposed to address these challenges.

Conclusions:

• LSLOD can facilitate the integration of biomedical data and knowledge.
• Overcoming LSLOD challenges can lead to scalable, intelligent infrastructures.
• These infrastructures can support AI methods for better clinical outcomes and research quality.