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      Is Open Access

      The Number of Scholarly Documents on the Public Web

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      PLoS ONE
      Public Library of Science

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          Abstract

          The number of scholarly documents available on the web is estimated using capture/recapture methods by studying the coverage of two major academic search engines: Google Scholar and Microsoft Academic Search. Our estimates show that at least 114 million English-language scholarly documents are accessible on the web, of which Google Scholar has nearly 100 million. Of these, we estimate that at least 27 million (24%) are freely available since they do not require a subscription or payment of any kind. In addition, at a finer scale, we also estimate the number of scholarly documents on the web for fifteen fields: Agricultural Science, Arts and Humanities, Biology, Chemistry, Computer Science, Economics and Business, Engineering, Environmental Sciences, Geosciences, Material Science, Mathematics, Medicine, Physics, Social Sciences, and Multidisciplinary, as defined by Microsoft Academic Search. In addition, we show that among these fields the percentage of documents defined as freely available varies significantly, i.e., from 12 to 50%.

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          Is Open Access

          Self-Selected or Mandated, Open Access Increases Citation Impact for Higher Quality Research

          Background Articles whose authors have supplemented subscription-based access to the publisher's version by self-archiving their own final draft to make it accessible free for all on the web (“Open Access”, OA) are cited significantly more than articles in the same journal and year that have not been made OA. Some have suggested that this “OA Advantage” may not be causal but just a self-selection bias, because authors preferentially make higher-quality articles OA. To test this we compared self-selective self-archiving with mandatory self-archiving for a sample of 27,197 articles published 2002–2006 in 1,984 journals. Methdology/Principal Findings The OA Advantage proved just as high for both. Logistic regression analysis showed that the advantage is independent of other correlates of citations (article age; journal impact factor; number of co-authors, references or pages; field; article type; or country) and highest for the most highly cited articles. The OA Advantage is real, independent and causal, but skewed. Its size is indeed correlated with quality, just as citations themselves are (the top 20% of articles receive about 80% of all citations). Conclusions/Significance The OA advantage is greater for the more citable articles, not because of a quality bias from authors self-selecting what to make OA, but because of a quality advantage, from users self-selecting what to use and cite, freed by OA from the constraints of selective accessibility to subscribers only. It is hoped that these findings will help motivate the adoption of OA self-archiving mandates by universities, research institutions and research funders.
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            Open access: The true cost of science publishing.

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              Accessibility of information on the web.

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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                9 May 2014
                : 9
                : 5
                : e93949
                Affiliations
                [1 ]Computer Science and Engineering, The Pennsylvania State University, University Park, Pennsylvania, United States of America
                [2 ]Information Sciences and Technology, The Pennsylvania State University, University Park, Pennsylvania, United States of America
                Wayne State University, United States of America
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: CLG MK. Performed the experiments: CLG MK. Analyzed the data: CLG MK. Contributed reagents/materials/analysis tools: CLG MK. Wrote the paper: CLG MK.

                Article
                PONE-D-13-40974
                10.1371/journal.pone.0093949
                4015892
                24817403
                8d26f922-5af0-443f-b6b4-e69f65654945
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 7 October 2013
                : 10 March 2014
                Page count
                Pages: 6
                Funding
                This work was partially funded by the National Science Foundation, grants 0958143, 1348712, and 1143921. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. There has been no additional external funding received for this study.
                Categories
                Research Article
                Computer and Information Sciences
                Information Technology
                Databases
                Text Mining
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Statistical Methods
                Research and Analysis Methods
                Research Assessment
                Bibliometrics
                Publication Practices
                Research Monitoring
                Science Policy
                Science Education
                Social Sciences
                Sociology
                Communications

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                Uncategorized

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