The Web of Science Author Impact Beamplot was recently released as a visualization tool by Martin Szomszor, Director of Clarivate's Institute for Scientific Information, in a March 2021 blog post. The Beamplot is meant to “showcase the range of a researcher’s publication and citation impact in a single data exhibit.”

For more information and how to calculate an Author Impact Beamplot, download the whitepaper from Clarivate: https://discover.clarivate.com/beamplots-whitepaper

Quotations and graphic used with permission from Clarivate’s March 1, 2021 Blog Post: “The Web of Science Author Impact Beamplots: A new tool for responsible research evaluation,” by Martin Szomszor.

• Uses a field-normalized citation metric (i.e., benchmarked against other similar publications from the same discipline and time frame)
• Does not unduly penalize researchers with gaps in their publication record
• Does not disadvantage those who work in fields with distinctly different publication activity
• Shows the volume and citation impact of an individual’s publication portfolio through time compared to the h-index, which tends to favor senior researchers that work in the physical sciences
• Each paper’s citation count is normalized and measured as a percentile.
• It is not necessarily biased against individuals who have taken a career break or published less at any given time.

Quotations and graphic used with permission from Clarivate’s March 1, 2021 Blog Post: “The Web of Science Author Impact Beamplots: A new tool for responsible research evaluation,” by Martin Szomszor.

“Importantly, beamplots reveal the data behind composite scores such as the h-index, show the underlying data on a paper-by-paper basis and provide a picture of performance over time. Seeing the data in this way puts a researcher’s publications into a context suitable for comparison and unpacks the citation performance of their publication portfolio.

The data visualized in beamplots steer [researchers] away from reduction to a single-point metric and force [them] to consider why the citation performance is the way it is.

Beamplots are particularly good at surfacing variation in the data that should be investigated and compared against other quantitative and qualitative indicators. In this way, they are a useful narrative tool that can refute or corroborate other evaluation criteria. …A beamplot, [when used responsibly], will help remove the current dependence on existing single-point metrics, eliminate indicator impoverishment and raise awareness of responsible research evaluation practices.”

Quotations and graphic used with permission from Clarivate’s March 1, 2021 Blog Post: “The Web of Science Author Impact Beamplots: A new tool for responsible research evaluation,” by Martin Szomszor.