November highlights from the world of scientific publishing

2nd Dec 2013

Some of what I learned this month from Twitter: new preprint server, Google Scholar Library, papers on citations and p-values, and the most networked science conference ever

BioRxiv

In what could be a major development in the culture of publishing, a preprint server for biology, BioRxiv, was launched this month. It is based on the long-running arXiv preprint server used by physicists (and increasingly quantitative biologists). Nature News had a good summary.

Google Scholar Library

Google Scholar have launched a new service, Google Scholar Library (h/t @phylogenomics). This is meant to be a way to organize papers you read or cite, so it could be a competitor to reference managers such as Mendeley and Zotero. However, it doesn’t seem to be fully set up for citing papers yet: you can import into BibTeX, EndNote, RefMan and RefWorks (but not Mendeley or Zotero) or get a single citation in just MLA, APA or Chicago style.

“Top researchers” and their citations

Two papers of particular interest this month: the first actually came out in late October and is entitled “A list of highly influential biomedical researchers, 1996–2011” (European Journal of Clinical Investigation; h/t @TheWinnower). The paper, by  John Ioannidis and colleagues (who also published the influential “Why Most Published Research Findings Are False” paper), sorted biomedical authors in Scopus by their h-index and total citations and listed various pieces of information for the top 400 by this measure. I found this interesting for several reasons, including:
  • It gives a feeling for what makes a high h-index: of over 15 million authors, about 1% had an h-index of over 20, about 5000 over 50 and only 281 over 80.
  • It shows how different sources of citation data can give different h-indices for the same author (see Table 3 in the paper; as pointed out by @girlscientist)

The paper is limited by its reliance on citation data and the h-index alone, so should not be taken too seriously, but it is worth a look if you haven’t already seen it.

p-values vs Bayes factors

The second is a paper in PNAS by Valen Johnson (covered by Erika Check Hayden in Nature News) suggested that the commonly used statistical standard of a p-value less than 0.05 is not good enough – in fact, around a quarter of findings that are significant at that level may be false. This conclusion was reached by developing a method to make the p-value directly comparable with the Bayes factor, which many statisticians prefer. As I’m not a statistician I’m not in a position to comment on the Bayesian/frequentist debate, but it is worth noting that this paper recommends a p-value threshold of less than 0.005 to be really sure of a result. A critical comment by a statistician is here (via @hildabast).

SpotOn London

Finally,  the main event of November for me was SpotOn London (#solo13), a two-day conference on science communication: policy, outreach and tools. This is one of the most connected conferences you can imagine: every session was live-streamed, the Twitter backchat was a major part of the proceedings, and many people followed along and joined in from afar. The session videos can all be viewed here.
For me four sessions were particular highlights:
  • The keynote talk by Salvatore Mele of CERN. This was not only an accessible explanation of the search for the Higgs Boson, and of the importance of open access and preprint publishing in high energy physics, but also a masterclass in giving an entertaining and informative presentation.
  • The discussion session Open, Portable, Decoupled – How should Peer Review change? (Storify of the tweets here)
  • The discussion session Altmetrics – The Opportunities and the Challenges (summary and some related links from Martin Fenner here)
  • A workshop I helped with, on rewriting scientific text using only the thousand mostly commonly used words in the English language (report by the organiser, Alex Brown, here)

Tags: 

Leave a Reply