Metrics: Researcher Metrics

Researcher metrics are quantitative metrics based on citation counting for an individual researcher. There are down sides to relying on research metrics to evaluate a researcher's impact. For example, as it would only cover certain content and may exclude content outside academic papers such as posters, blogs, podcasts and other non-traditional academic outputs. The most commonly used metric is the H-index.

The h-index is the most commonly used metric for individual researchers. It was developed by Jorg E. Hirsch in 2005 and who claimed it accounted for both quality and quantity in researcher's output. Use of the h-index is controversial and not supported by DORA signatories for the purposes of hiring.

The h-index is calculated by combining two factors: the number of papers a researcher has created and the number of citations each paper has received. The papers are arranged in descending order by number of citations. The h index is calculated by the number of papers (h) that have with at least that many (h) citations. For example if Bilbo Baggins has a h-index of 5 he has produced at least 5 papers that have been cited at least 5 times each. See our chart for a visual example.

The h-index for a single researcher will vary between different databases (e.g., Web of Science, Scopus, Google Scholar) because their underlying data sources are different.

The use of the h-index is controversial and it has several significant limitations: 

• Favours researchers with longer careers, as they have had more time to accumulate publications and citations.
• Can't compare researchers across different disciplines due to varying citation patterns.
• Doesn't account for author placement (e.g., first or last author).
• Can be "gamed" through self-citation.
• Provides a narrow view of a researcher's total output, as it mainly considers only citation data for journal articles and some books. Outputs such as, datasets, software, policy documents etc. are excluded.  

To get a fuller picture of a researcher's impact, it's essential to look beyond a single number like the h-index. A great quantity of research output such as posters, podcasts, data, and contributions to policy will not be included in the h-index.

Some other tools that can help look at the author's broader impact include:

Author Impact Beamplots (Web of Science): These visualisations show a researcher's publication performance over time, comparing each paper's citation count to the average for similar papers, providing valuable context beyond a single metric.

Author Metrics (Scopus): Scopus provides a dashboard with more data points, including information on collaborations and how many documents are in top-cited journals.

For information on other author level metrics read Bihari, A., Tripathi, S., & Deepak, A. (2023). 'A review on h-index and its alternative indices'. Journal of Information Science, 49(3), pp. 624-665. Available at: https://doi.org/10.1177/01655515211014478

See the below chart to see how Bilbo Baggins H-index was calculated. In this scenario, Bilbo has a H-index of 5.

The following databases allow you to calculate a researcher's h-index.