Bibliometric Data on Top 50 African Ophthalmologists
Description
This dataset supports a bibliometric study aimed at identifying and analyzing the most prolific ophthalmology researchers affiliated with African medical schools. To develop this dataset, we first compiled a comprehensive list of over 100 African medical schools known to have ophthalmology departments or faculties. Using Scopus, we executed a structured search strategy that combined general ophthalmic terms (e.g., “cataract,” “glaucoma,” “myopia,” “diabetic retinopathy”) with each institution's name. We manually reviewed and verified the resulting author affiliations and publication relevance in two screening phases to ensure the inclusion of only active ophthalmology researchers with current or past institutional ties to African medical schools. The dataset comprises 50 top-ranked researchers and includes key bibliometric metrics such as Scopus Author ID, affiliated institution, country, sex, h-index, total citations, publication count, and active publishing span. We also collected additional non-ranking attributes for deeper academic profiling—namely SciVal Topic prominence, highest academic qualifications, and academic rank. The dataset was last updated on March 31, 2025, and stored in a structured Excel format to enable consistent referencing and analysis. The dataset offers valuable insights into geographic distribution, research productivity, and subject area concentration of ophthalmic research in Africa.
Files
Steps to reproduce
To reproduce this dataset, begin by compiling a current list of accredited medical schools in Africa with ophthalmology departments. Next, access the Scopus database and conduct individual searches using ophthalmology-related keywords (e.g., “cataract,” “glaucoma,” “diabetic retinopathy,” “myopia”) in the title, abstract, and keyword fields. In the affiliation field, enter each medical school's name separately. Manually screen the results to ensure the relevance of each article to ophthalmology and verify that each author is affiliated with an African institution at the time of publication. Extract bibliometric data for eligible authors, including full name, Scopus Author ID, institution, country, sex, h-index, citation count, number of publications, and publishing span. Supplement this with additional information from Elsevier’s SciVal (e.g., top topics, academic qualifications, and current ranks). Consolidate the extracted data into a structured spreadsheet, ensuring standardization and avoiding duplicates. Time-stamp the dataset to reflect the date of data retrieval to maintain consistency.
Institutions
- University of Cape Coast