[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 As with last year (2009), the metrics used in this combat sport are already a year out of date.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
- 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
- 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
- Van Noorden, R. (2010). Metrics: A profusion of measures Nature, 465 (7300), 864-866 DOI: 10.1038/465864a
- 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
- 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 ]
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