O'Really?

June 22, 2010

Impact Factor Boxing 2010

Golden Gloves Prelim Bouts by Kate Gardiner[This post is part of an ongoing series about impact factors. See this post for the latest impact factors published in 2012.]

Roll up, roll up, ladies and gentlemen, Impact Factor Boxing is here again. As with last year (2009), the metrics used in this combat sport are already a year out of date. But this doesn’t stop many people from writing about impact factors and it’s been an interesting year [1] for the metrics used by many to judge the relative value of scientific work. The Public Library of Science (PLoS) launched their article level metrics within the last year following the example of BioMedCentral’s “most viewed” articles feature. Next to these new style metrics, the traditional impact factors live on, despite their limitations. Critics like Harold Varmus have recently pointed out that (quote):

“The impact factor is a completely flawed metric and it’s a source of a lot of unhappiness in the scientific community. Evaluating someone’s scientific productivity by looking at the number of papers they published in journals with impact factors over a certain level is poisonous to the system. A couple of folks are acting as gatekeepers to the distribution of information, and this is a very bad system. It really slows progress by keeping ideas and experiments out of the public domain until reviewers have been satisfied and authors are allowed to get their paper into the journal that they feel will advance their career.”

To be fair though, it’s not the metric that is flawed, more the way it is used (and abused) – a subject covered in much detail in a special issue of Nature at http://nature.com/metrics [2,3,4,5]. It’s much harder than it should be to get hold of these metrics, so I’ve reproduced some data below (fair use? I don’t know I am not a lawyer…) to minimise the considerable frustrations of using Journal Citation Reports (JCR).

Love them, loathe them, use them, abuse them, ignore them or obsess over them … here’s a small selection of the 7347 journals that are tracked in JCR  ordered by increasing impact.

Journal Title 2009 data from isiknowledge.com/JCR Eigenfactor™ Metrics
Total Cites Impact Factor 5-Year Impact Factor Immediacy Index Articles Cited Half-life Eigenfactor™  Score Article Influence™ Score
RSC Integrative Biology 34 0.596 57 0.00000
Communications of the ACM 13853 2.346 3.050 0.350 177 >10.0 0.01411 0.866
IEEE Intelligent Systems 2214 3.144 3.594 0.333 33 6.5 0.00447 0.763
Journal of Web Semantics 651 3.412 0.107 28 4.6 0.00222
BMC Bionformatics 10850 3.428 4.108 0.581 651 3.4 0.07335 1.516
Journal of Molecular Biology 69710 3.871 4.303 0.993 916 9.2 0.21679 2.051
Journal of Chemical Information and Modeling 8973 3.882 3.631 0.695 266 5.9 0.01943 0.772
Journal of the American Medical Informatics Association (JAMIA) 4183 3.974 5.199 0.705 105 5.7 0.01366 1.585
PLoS ONE 20466 4.351 4.383 0.582 4263 1.7 0.16373 1.918
OUP Bioinformatics 36932 4.926 6.271 0.733 677 5.2 0.16661 2.370
Biochemical Journal 50632 5.155 4.365 1.262 455 >10.0 0.10896 1.787
BMC Biology 1152 5.636 0.702 84 2.7 0.00997
PLoS Computational Biology 4674 5.759 6.429 0.786 365 2.5 0.04369 3.080
Genome Biology 12688 6.626 7.593 1.075 186 4.8 0.08005 3.586
Trends in Biotechnology 8118 6.909 8.588 1.407 81 6.4 0.02402 2.665
Briefings in Bioinformatics 2898 7.329 16.146 1.109 55 5.3 0.01928 5.887
Nucleic Acids Research 95799 7.479 7.279 1.635 1070 6.5 0.37108 2.963
PNAS 451386 9.432 10.312 1.805 3765 7.6 1.68111 4.857
PLoS Biology 15699 12.916 14.798 2.692 195 3.5 0.17630 8.623
Nature Biotechnology 31564 29.495 27.620 5.408 103 5.7 0.14503 11.803
Science 444643 29.747 31.052 6.531 897 8.8 1.52580 16.570
Cell 153972 31.152 32.628 6.825 359 8.7 0.70117 20.150
Nature 483039 34.480 32.906 8.209 866 8.9 1.74951 18.054
New England Journal of Medicine 216752 47.050 51.410 14.557 352 7.5 0.67401 19.870

Maybe next year Thomson Reuters, who publish this data, could start attaching large government health warnings (like on cigarette packets) and long disclaimers to this data? WARNING: Abusing these figures can seriously damage your Science – you have been warned!

References

  1. Rizkallah, J., & Sin, D. (2010). Integrative Approach to Quality Assessment of Medical Journals Using Impact Factor, Eigenfactor, and Article Influence Scores PLoS ONE, 5 (4) DOI: 10.1371/journal.pone.0010204
  2. Abbott, A., Cyranoski, D., Jones, N., Maher, B., Schiermeier, Q., & Van Noorden, R. (2010). Metrics: Do metrics matter? Nature, 465 (7300), 860-862 DOI: 10.1038/465860a
  3. Van Noorden, R. (2010). Metrics: A profusion of measures Nature, 465 (7300), 864-866 DOI: 10.1038/465864a
  4. Braun, T., Osterloh, M., West, J., Rohn, J., Pendlebury, D., Bergstrom, C., & Frey, B. (2010). How to improve the use of metrics Nature, 465 (7300), 870-872 DOI: 10.1038/465870a
  5. Lane, J. (2010). Let’s make science metrics more scientific Nature, 464 (7288), 488-489 DOI: 10.1038/464488a

[Creative Commons licensed picture of Golden Gloves Prelim Bouts by Kate Gardiner ]

October 24, 2008

PNAS envy?

Filed under: publishing — Duncan Hull @ 6:02 am
Tags: , , , , , , ,

Lincoln with Stars & Stripes by tanakawhoThe United States National Academy of Sciences (NAS) is an “honorific society of distinguished scholars engaged in scientific and engineering research, dedicated to the furtherance of science and technology and to their use for the general welfare”. Set up by none other than Abraham Lincoln himself, the academy publishes a prestigious scientific journal, called the Proceedings of the National Academy of Sciences, better known as just “PNAS” and available at www.pnas.org. This publication is  part of a supposedly elite club of high-profile journals – Nature, Science and PNAS (NSPNAS) – that many scientists from all around the world, strive to publish in. Now, there are those that think the world would be a better place if we concentrated on what scientists have to say, rather than where they say it. But currently, life doesn’t always work that way. Better journals, usually tend to have better reviewers and these are often the most important places to publish results. (more…)

April 13, 2007

Collaboration, collaboration, collaboration!

Geldof Blair collaborationWhat should your three main priorities be as a Scientist? Collaboration, collaboration, collaboration. Quentin Vicens and Phil Bourne have just published Ten Simple Rules for a Successful Collaboration [1] to help you do just that, as part of a continuing series [2,3,4,5].

Tony Bliar once said “Ask me my three main priorities for government, and I tell you: education, education, education.” In Science, its not so much about education as collaboration, collaboration, collaboration. The advice in Ten Simple Rules is all useful stuff, but what caught my eye is the fact that collaboration is on the rise, at least according to the number of co-authors on papers published in PNAS. The average number of co-authors has risen from 3.9 in 1981 to 8.4 in 2001. So before you publish or perish, it seems likely that you’ll also need to collaborate or commiserate… less laboratory, more collaboratory!

Photo credit Garret Keogh

References

  1. Quentin Vicens and Phillip Bourne (2007) Ten Simple Rules for a Successful Collaboration PLOS Computational Biology
  2. Phillip Bourne (2006) Ten Simple Rules for Getting Published PLOS Computational Biology
  3. Philip Bourne and Iddo Friedberg (2006) Ten Simple Rules for Selecting a Postdoctoral Position PLOS Computational Biology
  4. Phillip Bourne and Leo Chalupa (2006) Ten Simple Rules for Getting Grants PLOS Computational Biology
  5. Phillip Bourne and Alon Korngreen (2006) Ten Simple Rules for Reviewers PLOS Computational Biology
  6. This post originally published on nodalpoint with comments

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February 22, 2007

NSPNAS: Nature, Science or PNAS?

Filed under: publishing,Uncategorized — Duncan Hull @ 10:19 pm
Tags: , ,

A crude score for benchmarking scientists

TIM Have you ever wanted to compare different scientists by their publication record? It’s not always an easy task, but here is a crude and handy way to benchmark people by their journal publications in Nature, Science or PNAS using PubMed. Let’s call it the NSPNAS score, it’s not the h-index and it’s far from perfect, but it can be useful.

Imagine these scenarios:

  1. You’re a young scientist comtemplating who to do an undergraduate project, Masters degree or PhD with.
  2. You’ve finished your PhD and are wondering which lab could be your Stairway to PostDoc Heaven [1].
  3. You’re lucky enough to have landed a faculty position and you want to check the credibility of your new colleagues.
  4. You want to do some industrial espionage on your competitors in different labs around the world.
  5. You’re a Scientist dammit, and naturally you’re a curious person who just likes to measure things.

In any of these situations, you’ll probably want to look up the people concerned using Google Scholar which will give you a good idea of their research history. But you’re not interested in publications in the Journal of Few Subscribers or the Proceedings of the Boring Incomprehensible Nonsense Society (BINS), even if Google Scholar lists hundreds of their citations. Instead, you care about counting the Big Bang impact publications they have in the über-journals: Nature, Science and PNAS. You can find these publications in PubMed with this simple query:

Surname +Initials[au]+(nature[journal] or science[journal] or Proc Natl Acad Sci U S A[journal])

…and you can obviously modify this query to include popular journals from your own field as appropriate.

Where NSPNAS works

Note, NSPNAS scores were correct at the time of writring in 2007, but will change over time.

When you substitute an authors name and initials into the beginning of that query, you get your NSPNAS score. So Systems Biologist Douglas Kell for example, surname and initials “Kell+D[au]”, has an NSPNAS score of 6.

If the person in question has a unique or unusual surname and initials, its fairly easy to find their score: Nodalpointer Chris Mungall has an NSPNAS score of two while nodalpointer Jason Stajich has an NSPNAS score of three. These results suggest a positive correlation between Californian sunshine and NSPNAS. Meanwhile, back in rainy old Britain, Ensemblian Ewan Birney scores a formidable sixteen, which is just scary for a bloke in his thirties.

Where NSPNAS doesn’t work

Unfortunately, authors with common names like John Smith (who has more than 340 hits) can’t be easily benchmarked with this type of query, without trawling through hundreds of false positives. More importantly, some influential scientists score very low or zero, despite the fact that their work has been important in the world of biomedical science an beyond. This is especially true for Computer Scientists, Mathematicians and Informaticians, for example:

Many important members of the Dead Scientists Society also have low NSPNAS scores…

Conclusions

All these statistics remind us that many important ideas, techniques and results are not published in Nature, Science or PNAS and others are excluded from the PubMed index completely. It also confirms what we already know about peer-reviewed Journal publications not being the be-all and end-all of Engineering, Science or Medicine [3]. But NSPNAS still has its uses, provided the people you’re benchmarking have a rare name and didn’t snuff it before the PubMed index starts.

What is your NSPNAS score? If like me, you score a spectacular “nul points”, console yourself with the fact that you’re in good company with that score and given time, maybe you can change it.

References

  1. Jimmy Page and Robert Plant (1971) Stairway to Heaven
  2. Most of the Clay Mathematics Institute Millenium Prizes are still up for grabs if you get disillusioned with bioinformatics, fancy some fame and winning a million dollar fortune!
  3. Michael Seringhaus and Mark Gerstein (2007) Publishing perishing? Towards tomorrow’s information architecture BMC Bioinformatics 2007, 8:17 DOI:10.1186/1471-2105-8-17
  4. This post originally on nodalpoint, with comments

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