Data Sheet 2_A bibliometric and text-mining analysis of lipidomics and metabolomics in hum

9,628 scientific articles from 2004 to 2024 were harmonized and analyzed to map the evolution of lipidomics and metabolomics. The analysis, conducted by Alejandro I. Trejo-Castro, reveals an annual growth rate of 32.6% and identifies leading countries, journals, and emerging topics like AI and multi-omics integration. Data was sourced from Scopus and validated against Web of Science and PubMed.

Use Cases

• Analyze research productivity and collaboration networks based on author, institution, and country data.
• Map thematic evolution and identify emerging topics like artificial intelligence and Mendelian randomization based on keyword dynamics.
• Validate bibliometric indicators by comparing trends across multiple scientific databases mentioned in the methodology.

Strengths

• Includes 9,628 harmonized articles providing a substantial corpus for analysis.
• Covers a 20-year time range from 2004 to 2024, allowing for longitudinal trend analysis.
• Methodology involved cross-database validation using Scopus, Web of Science, and PubMed.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for specific analytical tasks.
• The dataset is small at 71.6 KB, indicating it contains summary or processed metrics rather than raw article text.

Provenance

Source

figshare, authored by Alejandro I. Trejo-Castro.

Collection Method

Bibliometric and text-mining analysis of articles from Scopus, with validation searches in Web of Science and PubMed.

Time Range

2004 to 2024

Freshness

Last updated 2026-05-19 04:25:20

Geography

Global, with leading contributions from the United States, China, and Europe.