Data Sheet 1_A bibliometric and text-mining analysis of lipidomics and metabolomics in hum

Alejandro I. Trejo-Castro's dataset contains bibliometric and text-mining analysis results for 9,628 scientific articles on lipidomics and metabolomics in human disease from 2004 to 2024. The data was harmonized and analyzed using Bibliometrix, Scimago Graphica, OpenRefine, and custom R scripts. It was last updated on 2026-05-19.

Use Cases

• Analyze publication trends and annual growth rates based on the 32.6% growth figure mentioned in the description
• Identify leading countries, journals, and authors in lipidomics/metabolomics based on the bibliometric indicators described
• Map thematic structures and emerging topics like AI and multi-omics integration based on the semantic mapping approach described
• Validate cross-database trends in scientific production based on the Web of Science and PubMed comparative validation mentioned

Strengths

• Analysis is based on 9,628 harmonized articles, providing a defined corpus
• Methodology includes cross-validation across Scopus, Web of Science, and PubMed databases
• Covers a 20-year time range from 2004 to 2024, allowing for longitudinal trend analysis

Limitations

• Dataset is small at 32.1 KB, indicating limited raw data or highly summarized results
• Column-level documentation is absent; field semantics must be inferred after download
• Row count is unknown, which may limit suitability assessment for certain analyses

Provenance

Source

figshare, authored by Alejandro I. Trejo-Castro

Collection Method

Bibliometric and text-mining analysis of scientific articles from Scopus, with validation against Web of Science and PubMed

Time Range

2004 to 2024

Freshness

Last updated 2026-05-19 04:25:19; freshness should be verified

Geography

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