Bibliometrics and Research Impact: Home

Types of bibliometric idicators:

• Quantity indicators - measure the productivity of a particular reasearcher.
• Quality indicators - measure the quality (or "performance") of a researcher's output.
• Structural indicators - measure connections between publications, authors, and areas of research.

Common metrics:

• Citation Count - the number of times a research output appears in the reference list of other documents (articles, books, reviews, conference proceedings, etc.). Found in:
  • Google Scholar,
  • Scopus
  • Web of Science.
• H-index - designed to measure an author's productivity and impact. It is the number of an author's publications (h) that have h or more citations to them. Found in:
  • Google Scholar
  • Scopus
  • Web of Science
• Field Normalized Citation Impact - the ratio between the actual citations reveived by a publication and the average number of citations received by all other similar publications. Found in: 
  • Scopus
• Relative Citation Ratio - a field-normalized indicator of influence, used by the NIH for evaluating the relative merits of biomedical research articles. Found in: 
  • NIH iCite
• Journal Impact Factor - based on the average number of citations received per paper published in that journal in the preceding two years. Found in:
  • Journal Citation Reports
• Outputs in Top Percentiles - the number or percentage of research outputs in the top most-cited publications in the work, United States, or another particular country. Found in:
  • Scopus
  • SciVal
• CiteScore - the average number of citations received in a calendar year by all items published in that journal in the preceding three years. Found in:
  • Scopus
• SCImago Journal Rank - places a higher value on citations from more prestigious journals. Found in:
  • Scopus
• Scopus SNIP - a ratio of a journa'ls citation count per paper and the citation potential in its subject field. It normalizes citation rate subject differences. Found in:
  • Scopus

Considerations to keep in mind when evaluating bibliometrics:

• Quality - high citation counts may not indicate quality. For example, an article may be cited frequently because other authors are refuting its findings.
• Disciplinary patterns - some research areas cite papers more than others. Fore example, in medicine and health there is a strong culture of citing and using other articles to validate findings.
• Level of researcher experience - some metrics are higher for experienced researchers than those early in their career. It is important not to compare researchers who are at different stages in their careers.
• Database coverage - the sources used to gather publication data may index different journals. The results will vary depending on which database you use.

The Leiden Manifesto for Research Metrics:

1. Quantitative evaluation should support qualitative, expert assessment.
2. Measure performance against the research missions of the institution, group, or researcher.
3. Protect excellence in locally relevant research.
4. Keep data collection and analytical processes open, transparent, and simple.
5. Allow those evaluated to verify data and analysis.
6. Account for variation by field in publication and citation practices.
7. Base Assessment of individual researchers on qualitative judgment of their portfolio.
8. Avoid misplaced concreteness and false precision.
9. Recognize the systemic effects of assessment and indicators. 
10. Scrutinize indicators regularly and update them.