Download
the problem impact assessment of journals n.
Skip this Video
Loading SlideShow in 5 Seconds..
The problem: Impact Assessment of Journals PowerPoint Presentation
Download Presentation
The problem: Impact Assessment of Journals

The problem: Impact Assessment of Journals

147 Vues Download Presentation
Télécharger la présentation

The problem: Impact Assessment of Journals

- - - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

  1. The problem: Impact Assessment of Journals • Impact Factor is widely used (& often abused) to assess impact of journals (& individuals) • No single metric can ever capture the full picture of research impact • Impact Factor measures average citation performance – but what about top performance? • Also: Large journals cannot have high impact factors – see Physical Review Letters102, 060001 (2009) • We need metrics not to replace but to complement the Impact Factor • We propose the S-index: a time-sensitive H-index-like metric for journals The IF is the number of citations over a 2-year window,averaged over the whole journal. Not all papers are created equal!

  2. Introduce a new metric for the highly cited papers in a journal:S-index For a set of papers H-index: fullpublication window, fullcitation window S-index (for 2011): 2009-2010 publication window 2011citation window 2011 S index = maximum number S of papers, published in 2009-2010, cited more than S timesin 2011 H-index • • • • • • ‘07 ‘08 ‘09 ‘10 ‘11 ‘12 today S-index

  3. Manolis Antonoyiannakis • I am a Senior Assistant Editor in Physical Review Letters, a journal published by the American Physical Society. • I am also an Adjunct Research Associate Scientist at Columbia University. • From 2008-2010 I was the Scientific Advisor to Prof. FotisKafatos, the founding President of the European Research Council in London/Brussels. • I devote most of my time handling the peer review of manuscripts, part of my time in bibliostatistics. I am interested in the peer review process from a statistical and systemic perspective and in metrics that quantify the impact of research. More specifically, I am interested in:  • understanding and enhancing peer review using data analysis and statistical inference (improving the review workflow process; detecting bias or conflict of interest; creating & improving referee selection protocols and tools; producing & analyzing feedback on editorial decisions; qualitative & quantitative citation analysis; recognizing citation impact patterns; etc.) • metrics - and their limitations - that quantify the impact of scientific research (impact statistics of journals, individuals and groups)  • sociological effects influencing the impact of scientific work  • networks of referees and authors  • behavioral studies of scientists For more info, please visit www.bibliostatistics.org