What is Category Normalised Citation Impact (CNCI)?
Citation rates vary across disciplines, change over time and different publication types have different citation behaviours. For accuracy and fairness, citation data should be normalised ** by discipline, year and publication type, making it an unbiased indicator of impact.
CNCI can also apply across several subject areas although it is a more meaningful metric if it is only for a single subject area.
A CNCI of 1 would be on par with the average citations for the subject area; more than 1 would be above average; and anything below 1 would be less than average.
In this example below the researcher has a career CNCI of 1.34.
Field Weighed Citation Impact (FWCI) takes into account the differences in research behaviour by comparing the number of citations an article has received to the average number of citations for similar articles. It compares articles with the same publication year, type and from the same discipline drawing on citation data from the Scopus database.
Scopus provides the FWCI for each article with the document details. To view the FWCI, along with some other useful metrics go to the Metrics tab in the Document Record.
The percentile metric is similar showing how many citations a publication has received compared with other publications from the same publication year, of the same type and from the same discipline. e.g. if it is in the 99th percentile it has received more citations that 99% of the other publications of the same type, with the same research area from the same year.
It is possible to manually calculate the FWCI for a researchers output using this by determining the average of the FWCIs for all of a researchers output i.e. the sum of the FCWIs of a researcher’s articles divided by the number of articles.
In addition to citations, you can include esteem measures into any grant or promotion application.
The H-Index, proposed by Jorge Hirsch in 2005, looks at the number of articles by an author (or group) and the number of times those articles have been cited. It combines this data to produce a single number - the h-index.
The following presentation explains how to calculate the h-index, along with some of the limitations with it as a measure of research impact.