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Research Guides

Research Impact Metrics: Locating, Evaluating, and Using

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Welcome to the research impact metrics guide. This guide brings together tools and discusses approaches to help you measure and assess the impact of scholarly works, researchers, institutions/colleges/departments (e.g., using citation-based metrics), as well as discuss ways to contextualize those approaches to provide more meaningful metrics and better communicate the impact, quality, and productivity of your work and others for promotion and tenure dossiers, grant proposals, awards, rankings, etc.

Please feel free to schedule a consultation for additional assistance.

Overview

Research impact can be examined both quantitatively and qualitatively. Quantitative approaches often use citation-based metrics. Qualitative indicators are more varied (e.g., peer recognition involving invitations or awards, influence on policy and practice, noted contributions to the field, fellowships, etc.).

There is no one tool or approach when it comes to measuring research impact. All have their limitations. None are ideal. In general, quantitative citation-based metrics should be normalized using ratios or percentages to provide context. The journal impact factor should only be used to make claims about the quality of a publication venue and not the research itself. Please see the Responsible Use tab for more information about the responsible use of research impact metrics and related issues. 

Terminology and Further Reading

Metrics versus Indicators: These terms are often used to describe various measures used to assess and analyze scholarly publications, authors, journals, or institutions. While the terms are often used interchangeably, they can have subtle differences in meaning. A metric is a quantitative measure used to assess a particular aspect of scholarly activity, whereas an indicator is a specific measurement or observable factor that is used to represent a broader concept or phenomenon. Most metrics and indicators are really only proxies for what they are used to measure (e.g., impact, quality, productivity, etc.).