This is an interesting question and one for which there is no hard answer.
Scientists do about four different things (leaving out teaching).
They publish scientific papers, they train PhD students, they patent inventions and they raise funding for research.
Depending on how you view scientists, you might place a different weight on each of these pursuits.
Taking the scientific papers issue first. Back in the old days in Ireland, you got a pat on the back when you published a paper, but the emphasis seemed to me to be on numbers, rather than on quality. Not a lot of people published in the top journals - for many journals, particularly in biological disciplines, you probably needed to do expensive experiments and there wasn’t a lot of funding.
You can realistically measure the impact a paper has on the scientific community by recording the number of times that paper is cited by other papers. That is indeed one measure. However, taking the google viewpoint, a paper should be considered more important if it is cited itself by papers that are themselves highly cited (the Google ‘pagerank’ algorithm ranks a webpage according to how many other webpages link to it, but also gives weight to links from pages that are themselves highly connected on the web).
So, raw counts of citations might be interesting or a more sophisticated algorithm might be employed in order to try to measure quality.
There are two kinds of papers - primary research and review articles. Review articles tend to be more highly cited as they act as a surrogate for a lot of papers that are in the review and they provide a one-stop solution, particularly when journals don’t allow you to put in an infinite number of citations, you can use a review article as a citation for a number of statements.
However, primary research is what drives innovation and knowledge, so perhaps citation analysis is not the way to go at all, or maybe it is, but we should leave out the reviews, but usually review articles are commissioned from the experts, so you wouldn’t be asked to write a review for a prestigious journal unless you were an expert, so why should your citation score be reduced just because you are the expert in the field.
Curious, no?
Journals get an “Impact factor” score (equation here).
We consider a good journal to have an impact factor of, maybe 3.0. The journal Science is something like 28 and Nature is not too different. Proceedings of the National Academy of sciences USA has an impact factor score of about 12. The last one is interesting. In a ranking of international journals according to Impact Factor score, this journal comes about 50th. However, using the Google PageRank algorithm, it is third - it is not cited as much as other journals, but the average paper citing it is itself a more highly-cited paper.
So, do we judge a scientist by the total number of papers? the total number of citations? some mixture?
What has emerged lately is the H-index. A scientists H-index is that you have published H papers that have been cited at least H times. This means that if you have a single run-away paper that is cited 1,000 times, but no other paper is ever cited, then your H-index is 1. Whereas if you have 10 papers that have been cited 10 times, your H-index is 10. the latter scientist has a much better H-index.
So, the H-index rewards consistency. It will tend to increase as you get older, so a proposed modification is to divide the H-index by the number of years since your first publication…giving your M-index. They say an M-index of 1 is a ’successful scientist’. An M-index of 2 indicated you are a top scientist and an M-index of 3 puts you in line for a Nobel Prize.
Kary Mulis won a nobel prize for inventing PCR. It was his Magnum Opus. There are not too many other papers he authored that were of major interest. He won a nobel prize for his one moment of inspiration. His H-index would have been pretty average, I think.
There are also people that work on the production line of genome projects, who have never written the grant applications or really driven the project and they have H-index scores of 25 or 30, despite only treating the job as a 9 to 5. So, if you want to increase your H-index, get on to a factory paper system.
This ranking of scientists and papers also doesn’t deal with one other issue - who was really driving the paper. The position of an author on a paper is of interest. The first and last author positions are generally considered to be the important places to be on a paper. Being put in the middle of a paper probably indicates you contributed knowledge or maybe some reagents, but you weren’t the driver of the publication.
So, how should we view somebody that is a co-author on a lot of well-cited papers, but their contribution to these papers was peripheral. Indeed, some scientists make entire careers out of being middle author on other people’s work, but still being able to claim that they have been cited many times.
So, who do I think is the best scientist in Ireland?
Prof. Seamus Martin, Professor of Human Genetics at TCD. From the preceding discussion, you will see that this is only an opinion and quite possibly using alternative criteria, you could say differently. However, his record of consistently producing extraordinarily high quality research would place him at the top - no disrespect to any other Irish scientist.

3 users commented in " How do we know if a scientist is good or not? "
Follow-up comment rss or Leave a TrackbackThat’s a really interesting summary James, thanks for that.
It reminds of a quote by Lord Acton, “We should judge talent when it’s at its best, and character when it’s at its worst“.
So if you were to publish one truly great paper, and a plethora of mediocrity you’d still count as a great scientist but if you skew the stats or invent the data just once, you’re a bad scientist forever.
It’s very refreshing to hear perspective from quite an accomplished scientist.
Hi Des. A lot of scientists indulge in stat-skewing somewhat - putting their buddies on their papers and the same in return etc. Hard to identify those situations, but if you have two scientists working closely together and each one putting the other on their respective papers, then very quickly you can double your apparent output.
Nice article - while not mentioned here, I know from my own discipline a major problem can also be “scientific snobbery”! It’s amazing what some just discount out of hand simply because it’s not a part of their scientific ‘worldview’/experience. So called new sciences (Computer Science, Bioinformatics etc.) tend to suffer a lot of this abuse, I’ve found.
Just my two cents!