These days I fount that for researchers, there are more ways to measure their value than just their number of citations and correlate with the impact factors of the journals where they publish. To be more exact, I found:
- h-index – The h index is a quantitative metric based on analysis of publication data using publications and citations to provide ‘an estimate of the importance, significance, and broad impact of a scientist’s cumulative research contributions’.
- article-level metrics – They are citation metrics which measure the usage and impact of individual scholarly articles .
To me, the h-index is an aggregator and offers a numeric quantifier for a researcher (a researcher with h-index 7 is less performant than one with h-index 15).
Article-level metrics (ALMs) have a more granular effect, in the sense that some people may be interested in a certain topic from a researcher, not all portfolio. Then, one can look at ALMs for the relevant titles.
ALMs, through their nature have more values you can search for. I’ve found:
- citations – number of citations for a specific article
- references – number of references for the article
- reads – the number of reads (e.g. downloads) for an article
- geographic coverage – where the article was read/downloaded/referred
- impact factor – the journal’s impact factor
Normally, I’d use h-index to give me a rough estimate of how ‘good‘ a researcher is. It’s easier to find out (it’s only one number). However, people actually interested in a person’s skills will probably look at ALMs.
The next article will detail my experience with ALMs.
A little experiment: If you find this post and ad below useful, please check the ad out :-)