Global Research Trends in Irrigation and Water Availability Dataset 2000–2024 A Scientometric Analysis

This dataset provides a curated collection of bibliographic records used in a scientometric analysis of global research trends in irrigation and water availability from 2000 to 2024. The dataset was developed to support the study entitled “Global research trends in irrigation and water availability using scientometric analysis for sustainable water management”. The data were retrieved from two major international scientific databases, Web of Science and Scopus, ensuring broad coverage of peer-reviewed literature. A structured Boolean search strategy was applied to identify publications at the intersection of irrigation practices, water resource management, and water availability, with emphasis on topics such as water use efficiency and precision agriculture. The dataset includes cleaned and standardized bibliographic metadata, such as authors, article titles, abstracts, keywords, publication year, journal names, citation counts, digital object identifiers (DOI), and country information (when available). Data processing involved merging records from different sources, removing duplicates, and harmonizing metadata using the Bibliometrix package in R. This dataset enables the replication of the scientometric analysis presented in the associated study and can be reused for further research on water resources, irrigation systems, sustainability, and global scientific collaboration networks. It is particularly relevant for studies addressing water security, climate change impacts on agriculture, and Sustainable Development Goal 6 (Clean Water and Sanitation). The dataset is provided in CSV format and accompanied by documentation describing the data structure, variables, and methodological procedures. Related Publication:Assane, C., Rodrigues, A. M., Rubio Neto, A., & da Silva Júnior, É. D. Global Research Trends in Irrigation and Water Availability: A Scientometric Analysis for Water Security and Sustainable Management. (under review) Notes:The dataset includes only English-language peer-reviewed articles and review papers indexed in Web of Science and Scopus databases. Other document types and regional databases were not included in this version.