Data Sheet 3_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 dataset, created by Alejandro I. Trejo-Castro, shows the field expanded at an annual growth rate of 32.6%. It identifies leading countries, core journals, and emerging topics like artificial intelligence and multi-omics integration.

Use Cases

• Analyze publication trends and growth rates in lipidomics/metabolomics based on the described 20-year time series.
• Map thematic structures and keyword dynamics based on the semantic and conceptual mapping methodology described.
• Identify leading journals, authors, and countries in the field based on the bibliometric indicators provided.
• Study the emergence of interdisciplinary bridges like microbiota-COVID-19 interactions based on the niche themes identified.

Strengths

• Analysis is based on 9,628 harmonized articles, providing a substantial corpus.
• Covers a 20-year time range from 2004 to 2024, allowing longitudinal study.
• Methodology includes cross-database validation with Web of Science and PubMed for robustness.
• Identifies specific growth rates (32.6% annual) and leading countries (United States, China).

Limitations

• The dataset file size is 220.0 B, indicating it likely contains only summary or metadata, not the full article corpus.
• 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.

Provenance

Source

Scopus, with validation searches in Web of Science Core Collection and PubMed.

Collection Method

Bibliometric and text-mining analysis using Bibliometrix, Scimago Graphica, OpenRefine, and custom R scripts.

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.