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Research Impact Metrics

Provides an overview of Research Impact Metrics

Using this guide

This guide is designed to help you understand and find your own research metrics, and generate metrics reports from available tools. 

This guide presents the tools available to track the quantitative influence of research publications. These quantitative measures include, but are not limited to, citation-based metrics like h-index, citation counts, field-weighted citation impact, etc., and alternative metrics to track influence in non-academic fields like mentions from social media and government policies. Research impact should also be demonstrated qualitatively in terms of economic, social and cultural applications and measures of esteem, there are some examples of these applications and measurements.

We endorse the responsible use of these measures as one of a range of indicators of research quality. Researcher and research metrics can be used to support the following activities under the instructions from relevant authorities: 

  • Applications for grant funding
  • Applications for promotion
  • Your research profile
  • Department and Faculty reviews and National Assessment exercises

 

 

Printable version 

Citation-based metrics are widely used as quantitative measurements to track the impact of research outputs. However there are considerations that need to be taken into account:

  • Quality vs. Quantity: high citation counts do not necessarily indicate high-quality research. Articles can be frequently cited for negative reasons, such as being controversial or flawed.
  • Field Variability: different academic fields have varying citation practices. For example, papers in the life sciences tend to receive more citations than those in the humanities, making cross-disciplinary comparisons challenging 
  • Database coverage: citation databases collect data from different sources and calculate their metrics differently. A journal you've published in might not be indexed by the main citation analysis tools.
  • Time lag: recent research articles may not yet have been cited by others.
  • Gaming the System: Some researchers may manipulate citation metrics through various means, such as excessive self-citation or strategic collaborations, so interpret the numbers with caution.

Using these metrics responsibly involves understanding and applying their limitations in a balanced and contextual manner. Here are some key guidelines:

  • Use Multiple Metrics: Rely on a combination of metrics rather than a single one to reduce bias and provide a more comprehensive view of research impact.
  • Use field normalized metrics to compare different disciplines. 
  • Contextualize the Data: Always interpret metrics within the context of the research field, publication year, and other relevant factors. 
  • Combine Quantitative and Qualitative Assessments: Metrics should complement, not replace, expert opinion and qualitative evaluations. 
  • Be Transparent: Clearly state the metrics used and their limitations when presenting your analysis.

Elsevier's Research Metrics Handbook explained the limitations of the metrics used in Scopus and SciVal, and provided suggestions about how to use these metrics in a contextual way:

Contact your Faculty or Clinical Librarians for assistance with:

  • Assessing your research impact
  • Using and comparing results from databases such as Scopus, Web of Science and Google Scholar
  • Identifying highly ranked journals in your field
  • Advice on strategic publishing
  • Managing your author profiles.

The library runs research workshops on strategic publishing, profile management, and using metrics tools, including SciVal, InCites, Altmetrics Explorer, etc. Registration is via myRDC.