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 As with last year (2009), the metrics used in this combat sport are already a year out of date.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!


  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 ]

December 11, 2009

The Semantic Biochemical Journal experiment

utopian documentsThere is an interesting review [1] (and special issue) in the Biochemical Journal today, published by Portland Press Ltd. It provides (quote) “a whirlwind tour of recent projects to transform scholarly publishing paradigms, culminating in Utopia and the Semantic Biochemical Journal experiment”. Here is a quick outline of the publishing projects the review describes and discusses:

  • Blogs for biomedical science
  • Biomedical Ontologies – OBO etc
  • Project Prospect and the Royal Society of Chemistry
  • The Chemspider Journal of Chemistry
  • The FEBS Letters experiment
  • PubMedCentral and BioLit [2]
  • Public Library of Science (PLoS) Neglected Tropical Diseases (NTD) [3]
  • The Elsevier Grand Challenge [4]
  • Liquid Publications
  • The PDF debate: Is PDF a hamburger? Or can we build more useful applications on top of it?
  • The Semantic Biochemical Journal project with Utopia Documents [5]

The review asks what advances these projects have made  and what obstacles to progress still exist. It’s an entertaining tour, dotted with enlightening observations on what is broken in scientific publishing and some of the solutions involving various kinds of semantics.

One conclusion made is that many of the experiments described above are expensive and difficult, but that the costs of not improving scientific publishing with various kinds of semantic markup is high, or as the authors put it:

“If the cost of semantic publishing seems high, then we also need to ask, what is the price of not doing it? From the results of the experiments we have seen to date, there is clearly a need to move forward and still a great deal of scope to innovate. If we fail to move forward in a collaborative way, if we fail to engage the key players, the price will be high. We will continue to bury scientific knowledge, as we routinely do now, in static, unconnected journal articles; to sequester fragments of that knowledge in disparate databases that are largely inaccessible from journal pages; to further waste countless hours of scientists’ time either repeating experiments they didn’t know had been performed before, or worse, trying to verify facts they didn’t know had been shown to be false. In short, we will continue to fail to get the most from our literature, we will continue to fail to know what we know, and will continue to do science a considerable disservice.”

It’s well worth reading the review, and downloading the Utopia software to experience all of the interactive features demonstrated in this special issue, especially the animated molecular viewers and sequence alignments.

Enjoy… the Utopia team would be interested to know what people think, see commentary on friendfeed,  the digital curation blog and youtube video below for more information.


  1. Attwood, T., Kell, D., McDermott, P., Marsh, J., Pettifer, S., & Thorne, D. (2009). Calling International Rescue: knowledge lost in literature and data landslide! Biochemical Journal, 424 (3), 317-333 DOI: 10.1042/BJ20091474
  2. Fink, J., Kushch, S., Williams, P., & Bourne, P. (2008). BioLit: integrating biological literature with databases Nucleic Acids Research, 36 (Web Server) DOI: 10.1093/nar/gkn317
  3. Shotton, D., Portwin, K., Klyne, G., & Miles, A. (2009). Adventures in Semantic Publishing: Exemplar Semantic Enhancements of a Research Article PLoS Computational Biology, 5 (4) DOI: 10.1371/journal.pcbi.1000361
  4. Pafilis, E., O’Donoghue, S., Jensen, L., Horn, H., Kuhn, M., Brown, N., & Schneider, R. (2009). Reflect: augmented browsing for the life scientist Nature Biotechnology, 27 (6), 508-510 DOI: 10.1038/nbt0609-508
  5. Pettifer, S., Thorne, D., McDermott, P., Marsh, J., Villéger, A., Kell, D., & Attwood, T. (2009). Visualising biological data: a semantic approach to tool and database integration BMC Bioinformatics, 10 (Suppl 6) DOI: 10.1186/1471-2105-10-S6-S19

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