As you may be aware, as part of our ongoing article-level metrics program, we provide a downloadable Excel file for the entire dataset (3 Mb zipped, but 35 Mb when unzipped). The first such file was created when we launched the usage data (in September 2009) and we have just updated it with the latest data (with data correct up to January 31st 2010). Going forwards, we plan to update this spreadsheet every other month, starting in April.

The main changes with this latest version (other than containing a more recent dataset) are:

• The addition of the ‘missing’ usage data for all our articles.
  • We now have a complete usage dataset for all articles, going back to day of publication (previously some articles missed the usage data for their early years)
• The addition of data from researchblogging.org. Researchblogging.org are a blog aggregating service and we now include their data as part of the article-level metrics data set (as described in an earlier post)
• An update to the various  journal level summary tables

Some people have already started analysing our data and we encourage anyone who is interested to take this dataset and do their own analysis. Also be aware that the ‘live’ data for each article can be accessed by clicking on the link: “Download raw Metrics data as XML” which can be found at the bottom of each article’s Metrics tab.

Several people blogged about the meeting, and Brian Glanz provided an excellent running commentary for the entire day.

Courtesy of Microsoft Research, the full video coverage of all the talks are now online as follows: Session 1 (Microsoft Research; Cameron Neylon; Jean-Claude Bradley); Session 2 (Antony Williams; Peter Murray-Rust); Session 3 (Heather Joseph; Stephen Friend); and Session 4 (starring myself, in a warm up role for the keynote by John Wilbanks).You will need to install Silverlight to view the videos.

This was an excellent meeting, for which Microsoft and Science Commons deserve a lot of praise – I recommend the video coverage for anyone who couldnt be there.

Today we learned that by the end of this week PLoS ONE (in keeping with all other PLoS journals) will be indexed by the Web of Science – this is an important literature discovery tool that many people use and so we are pleased to be indexed. PLoS ONE is also indexed by a host of other services such as PubMed, MEDLINE, PubMed Central, Scopus, Google Scholar, the Chemical Abstracts Service (CAS), EMBASE, AGRICOLA, PsycINFO, Zoological Records, FSTA (Food Science and Technology Abstracts), GeoRef, and RefAware.

Initially, coverage in the Web of Science will include new PLoS ONE articles plus those published in 2008 and 2009, and will be expanded to the articles published in 2006 (when PLoS ONE was launched) and 2007 in the coming weeks. Inclusion in the Web of Science also means that in June 2010 PLoS ONE will receive journal-level citation data from Thomson Reuters including a 2- and 5-year Impact Factor and Eigenfactor metrics.

As we have previously indicated, PLoS believes that research articles are best assessed on their own merits, rather than on the basis of the journal (and its impact factor) where the work happens to be published. While we are happy that PLoS ONE articles will become more discoverable as a result of their inclusion in the Web of Science, we will continue to push forward with our Article-Level Metrics program.

Naturally, we understand that inclusion in the Web of Science is significant for many academics whose research output is still measured by traditional means. We hope that this news encourages even more scientists to publish their work in PLoS journals, to benefit from the article-level metrics that are provided for every PLoS article (for example, this PLoS ONE article), and to ensure that all interested users have open access to their research.

To commemorate our birthday, we’ve selected ten papers published in our inaugural release on December 20, all of which highlight some of the usage data made available on all PLoS papers earlier this year as part of our article-level metrics programme. This is how they have performed in the various metrics over the past three years:

A Virtual Reprise of the Stanley Milgram Obedience Experiments
Mel Slater, Angus Antley, Adam Davison, David Swapp, Christoph Guger, et al.

The Evolution of Mammalian Gene Families
Jeffery P. Demuth, Tijl De Bie, Jason E. Stajich, Nello Cristianini, Matthew W. Hahn

Mesenchymal Stem Cell-Mediated Functional Tooth Regeneration in Swine
Wataru Sonoyama, Yi Liu, Dianji Fang, Takayoshi Yamaza, Byoung-Moo Seo, et al.

Taxonomic Reliability of DNA Sequences in Public Sequence Databases: A Fungal Perspective
R. Henrik Nilsson, Martin Ryberg, Erik Kristiansson, Kessy Abarenkov, Karl-Henrik Larsson, Urmas Kõljalg

Sexual Selection and the Evolution of Brain Size in Primates
Michael A. Schillaci

Perceptual Learning of Motion Leads to Faster Flicker Perception
Aaron R. Seitz, Jose E. Nanez, Sr., Steve R. Holloway, Takeo Watanabe

Concentration of the Most-Cited Papers in the Scientific Literature: Analysis of Journal Ecosystems
John P. A. Ioannidis

A Systems Biology Strategy Reveals Biological Pathways and Plasma Biomarker Candidates for Potentially Toxic Statin-Induced Changes in Muscle
Reijo Laaksonen, Mikko Katajamaa, Hannu Päivä, Marko Sysi-Aho, Lilli Saarinen, et al.

Multilocus Sequence Typing Breathes Life into a Microbial Metagenome
Eshwar Mahenthiralingam, Adam Baldwin, Pavel Drevinek, Elke Vanlaere, Peter Vandamme, et al.

Depauperate Avifauna in Plantations Compared to Forests and Exurban Areas
David G. Haskell, Jonathan P. Evans, Neil W. Pelkey

The presentation was recorded and so, by the power of multi-multi media, it is now available in many different formats – as a webcast (with both audio and video versions), as a YouTube video, and as a slidecast at MyPlick (incorporating audio, synced with the slides).

In addition, readers may be interested to learn that a FriendFeed room now exists for Article Level Metrics. We do not regard Article Level Metrics as a PLoS-only project and we hope (and expect) that other publishers will adopt the concepts that we are pioneering. Therefore, if was gratifying that this discussion forum was created by members of the community outside of PLoS.  It is being used as a place to collect and discuss issues of relevance to the concept of Article Level Metrics (i.e. it is not specific to PLoS)  and it is definitely worth subscribing to.

The powerpoint and synced audio can be found at Myplick, and the organisers also hope to put the full video of all presentations online sometime soon. My talk concentrated on PLoS ONE (as opposed to PLoS) – I went into some of our motivations and the reasons for our editorial criteria; quite a bit of detail on the PLoS Article-Level Metrics program; showed some sneak peeks of some upcoming features and finished up by demonstrating some of the power of Open Access in a world of interlinked databases. The audio includes approx 20 minutes of questions at the end, which also went into PLoS Currents: Influenza

In my opinion the presentation was… awesome!

Of particular relevance to PLoS ONE is the presentation by Mark Patterson (Publishing Director of PLoS) regarding PLoS’s efforts towards a “Re-engineering of the Scientific Journal”. In this presenation, Mark goes into considerable detail about PLoS ONE, about the PLoS Article-Level Metrics launch, and PLoS Currents: Influenza and it should make fascinating viewing for anyone interested in the innovative work we are doing in online publishing.

Mark Patterson Presenting to OASPA

]]> http://blogs.plos.org/everyone/2009/10/06/re-engineering-the-scientific-journal/feed/ 1 http://blogs.plos.org/everyone/2009/09/16/article-level-metrics-at-plos-%e2%80%93-addition-of-usage-data/ http://blogs.plos.org/everyone/2009/09/16/article-level-metrics-at-plos-%e2%80%93-addition-of-usage-data/#comments Wed, 16 Sep 2009 19:38:11 +0000 Peter Binfield http://everyone.plos.org/?p=2121 (cross posted from a blog made by Mark Patterson on the PLoS Blog)

As part of our ongoing article-level metrics program, we’re delighted to announce that all seven PLoS journals will now provide online usage data for published articles, going back to their date of original publication. With this addition, the suite of metrics on PLoS articles now includes measures of: online usage; citations from the scholarly literature; social bookmarks; blog coverage; and the Comments, Notes and ‘Star’ ratings that have been made on the article.

As discussed recently, we at PLoS feel that there is much to be gained from assessing research articles on their own merits rather than on the basis of the journal (and its impact factor) where the work happens to be published. Until recently, however, readers have simply not had suitable tools to give them any indication of the quality (or ‘impact’) of an individual article. With the advent of online publishing and a burgeoning array of third parties providing information on scholarly articles, it has finally become feasible to provide meaningful article-level metrics and indicators for readers.

PLoS has therefore embarked on a program to aggregate a range of available data about an article and place that data on the article itself. The data are found on the new tab called ‘Metrics’, available on all articles. A reader can now scan the various metrics to determine the extent to which the article has been viewed, cited, covered in the media and so forth. With the addition of usage data to the article-level metrics we have taken another step towards providing the community with valuable data that can be used and analyzed.

In order to make article-level metrics as open and useful as possible, we are providing our entire dataset as a downloadable spreadsheet and we encourage interested researchers to download the data and perform their own analyses. We will be updating this spreadsheet periodically, but on launch the data it contains are correct up to July 31st, 2009. Future developments in our article-level metrics program will include the provision of more data for each metric (whenever we can locate high quality sources) and new indicators as they arise, as well as the development of more sophisticated display and analysis tools on the site itself.

We believe that article-level metrics represent an important development for scholarly publishing. While some publishers are providing limited data, we are not aware of any publisher that has gone as far as PLoS in providing such a broad range of indicators and metrics, and in making the data openly available. We invite you to visit our journal sites and seek out the Metrics tab for each article.

It’s also important to emphasize that online usage should not be seen as an absolute indicator of quality for any given article, and such data must be interpreted with caution. To provide additional context and to aid interpretation, we have provided a series of summary tables indicating the average usage of categories of article (grouped by age, journal and topic area). Users will also notice that a number of articles do not have any usage data, because of problems with the log files. We are working hard to add data for these articles, and we also encourage readers to let us know if they find any anomalies or have any questions about the data.

More information about our article-level metrics program can be found in our FAQ as well as in this page of descriptive text for each journal (e.g for PLoS Biology and PLoS ONE). We look forward to your feedback, and to further developments in article-level metrics.

Mark Patterson, Director of Publishing

Media and other enquiries to Liz Allen, Director of Marketing, Tel (001) 415 624 1218

The discussion lasted about an hour and tackled various aspects of academic publishing in the internet era, open science, open access, how academics are measured and rewarded in the university tenure system, and our new developments in the area of Article-Level Metrics.

It can be accessed via Vimeo or at the original archive location and should be of interest to anyone interested in how academic publishing is changing today. I would like to thank Dr Kiki for the opportunity to appear and for the fascinating discussions that resulted.

Here’s the result of that collaboration. In the video Cameron explains how Article-Level Metrics can make your life easier by helping you to understand the quality and relevance of articles so that you can decide which articles are the most important for you to read. Cameron focuses in on the aspect of Article-Level Metrics relating to social bookmarking data, and explains how you can use this information to help in your research and discovery process. He also explains how you can contribute to making those metrics even stronger, to the benefit of all!

This is the first video in what we hope will be a series of ‘PLoS Conversations” and we hope you enjoy it.

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